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kernel
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Tag #kernel

818 papers:

ASPLOSASPLOS-2020-AngstadtJW #automaton #bound #learning #legacy #string
Accelerating Legacy String Kernels via Bounded Automata Learning (KA, JBJ, WW), pp. 235–249.
CGOCGO-2020-CowanMCBC #automation #generative #machine learning
Automatic generation of high-performance quantized machine learning kernels (MC, TM, TC, JB, LC), pp. 305–316.
ICSMEICSME-2019-LiYZ #linux
Application of Philosophical Principles in Linux Kernel Customization (HL, LY, XZ), p. 365.
FMFM-2019-SinghPDD #detection #static analysis
Static Analysis for Detecting High-Level Races in RTOS Kernels (AS, RP, DD, MD), pp. 337–353.
SEFMSEFM-2019-OliveiraCO #linux #performance #verification
Efficient Formal Verification for the Linux Kernel (DBdO, TC, RSdO), pp. 315–332.
CIKMCIKM-2019-HosseiniH #feature model #learning #multi #prototype #representation
Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection (BH, BH), pp. 1863–1872.
CIKMCIKM-2019-LiaoZ #online #sketching
Online Kernel Selection via Tensor Sketching (SL, XZ), pp. 801–810.
CIKMCIKM-2019-VazirgiannisNS #graph #machine learning
Machine Learning on Graphs with Kernels (MV, GN, GS), pp. 2983–2984.
CIKMCIKM-2019-XuZL #incremental #online #predict
New Online Kernel Ridge Regression via Incremental Predictive Sampling (SX, XZ, SL), pp. 791–800.
ICMLICML-2019-0002WF #clustering #complexity #query
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering (TY0, DPW, MF), pp. 7055–7063.
ICMLICML-2019-AgrawalTHB #interactive #performance
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions (RA, BLT, JHH, TB), pp. 141–150.
ICMLICML-2019-BiettiMCM #network
A Kernel Perspective for Regularizing Deep Neural Networks (AB, GM, DC, JM), pp. 664–674.
ICMLICML-2019-ChatterjiPB #learning #online
Online learning with kernel losses (NSC, AP, PLB), pp. 971–980.
ICMLICML-2019-Chen #analysis #bound #consistency #fault #nearest neighbour
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates (GHC), pp. 1001–1010.
ICMLICML-2019-DaoGRSSR
A Kernel Theory of Modern Data Augmentation (TD, AG, AR, VS, CDS, CR), pp. 1528–1537.
ICMLICML-2019-DereliOG #algorithm #analysis #biology #learning #multi
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology (OD, CO, MG), pp. 1576–1585.
ICMLICML-2019-HsuR
Bayesian Deconditional Kernel Mean Embeddings (KH, FR), pp. 2830–2838.
ICMLICML-2019-JitkrittumSGRHS
Kernel Mean Matching for Content Addressability of GANs (WJ, PS, MWG, AR, JH, BS), pp. 3140–3151.
ICMLICML-2019-KimSRW #adaptation #convergence
Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension (JK, JS, AR, LAW), pp. 3398–3407.
ICMLICML-2019-LiCW #algorithm #classification #linear #quantum #sublinear
Sublinear quantum algorithms for training linear and kernel-based classifiers (TL, SC, XW), pp. 3815–3824.
ICMLICML-2019-LimA #learning #markov #process #robust
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes (SHL, AA), pp. 3973–3981.
ICMLICML-2019-LiSSG #exponential #learning #product line
Learning deep kernels for exponential family densities (WL, DJS, HS, AG), pp. 6737–6746.
ICMLICML-2019-MeyerH #classification #performance #statistics
Optimality Implies Kernel Sum Classifiers are Statistically Efficient (RAM, JH), pp. 4566–4574.
ICMLICML-2019-OglicG #learning #scalability
Scalable Learning in Reproducing Kernel Krein Spaces (DO, TG0), pp. 4912–4921.
ICMLICML-2019-SiminelakisRBCL #evaluation
Rehashing Kernel Evaluation in High Dimensions (PS, KR, PB, MC, PL), pp. 5789–5798.
ICMLICML-2019-SlimCAV #framework #named
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection (LS, CC0, CAA, JPV), pp. 5857–5865.
ICMLICML-2019-TeradaY #normalisation
Kernel Normalized Cut: a Theoretical Revisit (YT, MY), pp. 6206–6214.
ICMLICML-2019-UurtioBR #analysis #canonical #correlation #scalability
Large-Scale Sparse Kernel Canonical Correlation Analysis (VU, SB, JR), pp. 6383–6391.
ICMLICML-2019-ZhangL #incremental #learning #online #random #sketching
Incremental Randomized Sketching for Online Kernel Learning (XZ, SL), pp. 7394–7403.
KDDKDD-2019-Li0WGYK #adaptation #learning #multi #predict
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points (ZL, JZ0, QW0, YG, JY, CK), pp. 2848–2856.
KDDKDD-2019-WuYHZX0JA #performance #random #string
Efficient Global String Kernel with Random Features: Beyond Counting Substructures (LW, IEHY, SH, LZ0, KX, LM0, SJ, CCA), pp. 520–528.
KDDKDD-2019-WuYZXZPXA #graph #random #scalability #using
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding (LW, IEHY, ZZ0, KX, LZ0, XP0, YX, CCA), pp. 1418–1428.
KDDKDD-2019-XuTZ #learning #multi
Isolation Set-Kernel and Its Application to Multi-Instance Learning (BCX, KMT, ZHZ), pp. 941–949.
PLDIPLDI-2019-GershuniAGNNRRS #linux #precise #static analysis
Simple and precise static analysis of untrusted Linux kernel extensions (EG, NA, AG, NN, JAN, NR, LR, MS), pp. 1069–1084.
ASEASE-2019-Gu00 #api #approach #graph #named
CodeKernel: A Graph Kernel Based Approach to the Selection of API Usage Examples (XG, HZ0, SK0), pp. 590–601.
ASEASE-2019-WenCC #linux #named
PTracer: A Linux Kernel Patch Trace Bot (YW, JC, SC), pp. 1210–1211.
ESEC-FSEESEC-FSE-2019-ShiWFWSJSJS #enterprise #fuzzing #industrial #linux
Industry practice of coverage-guided enterprise Linux kernel fuzzing (HS, RW, YF, MW, XS, XJ, HS, YJ0, JS), pp. 986–995.
ESEC-FSEESEC-FSE-2019-Tan #linux #maintenance #multi
Reducing the workload of the Linux kernel maintainers: multiple-committer model (XT), pp. 1205–1207.
ASPLOSASPLOS-2019-BaiLTH #automation #detection #fault #linux #named
DCNS: Automated Detection Of Conservative Non-Sleep Defects in the Linux Kernel (JJB, JL, WT, SMH0), pp. 287–299.
ASPLOSASPLOS-2019-OsterlundKOBBG #detection #execution #multi #named
kMVX: Detecting Kernel Information Leaks with Multi-variant Execution (, KK, PO, AB, HB, CG), pp. 559–572.
ASPLOSASPLOS-2019-PhothilimthanaE #data flow #gpu #synthesis
Swizzle Inventor: Data Movement Synthesis for GPU Kernels (PMP, ASE, AW0, AJ, BH, HB, SJK, VG, ET, RB), pp. 65–78.
CASECASE-2019-PengZZZ #analysis #component #detection #fault #markov #multi #process
Hidden Markov Model Combined with Kernel Principal Component Analysis for Nonlinear Multimode Process Fault Detection (PP, JZ, YZ, HZ), pp. 1586–1591.
CASECASE-2019-SharabianiBGND #algorithm #polynomial #using
A Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function (AS, AB, WLG, RN, HD), pp. 418–423.
CCCC-2019-LiuHWCL0X #compilation #concurrent #named #thread
PPOpenCL: a performance-portable OpenCL compiler with host and kernel thread code fusion (YL, LH, MW, HC, FL, XF0, JX), pp. 2–16.
CGOCGO-2019-MishraKC #automation #composition
Kernel Fusion/Decomposition for Automatic GPU-Offloading (AM, MK, BMC), pp. 283–284.
CGOCGO-2019-QiaoRHT #approach #locality #optimisation
From Loop Fusion to Kernel Fusion: A Domain-Specific Approach to Locality Optimization (BQ, OR, FH, JT), pp. 242–253.
ESOPESOP-2019-ChopraPD #static analysis
Data Races and Static Analysis for Interrupt-Driven Kernels (NC, RP, DD), pp. 697–723.
FASEFASE-2019-PengR #effectiveness #gpu #named
CLTestCheck: Measuring Test Effectiveness for GPU Kernels (CP, AR), pp. 315–331.
CAVCAV-2019-GuoLLRS #analysis #scheduling
Integrating Formal Schedulability Analysis into a Verified OS Kernel (XG, ML, ML0, LR, ZS), pp. 496–514.
MSRMSR-2018-XuZ #dataset #linux #multi
A multi-level dataset of linux kernel patchwork (YX, MZ), pp. 54–57.
SANERSANER-2018-XuLLZ #analysis #component #fault #hybrid #learning #predict
Cross-version defect prediction via hybrid active learning with kernel principal component analysis (ZX, JL0, XL, TZ0), pp. 209–220.
CIKMCIKM-2018-NikolentzosV #graph
Enhancing Graph Kernels via Successive Embeddings (GN, MV), pp. 1583–1586.
ICMLICML-2018-AlaaS18a #automation #learning #modelling #named #optimisation
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning (AMA, MvdS), pp. 139–148.
ICMLICML-2018-BalogTS #database
Differentially Private Database Release via Kernel Mean Embeddings (MB, IOT, BS), pp. 423–431.
ICMLICML-2018-BelkinMM #learning
To Understand Deep Learning We Need to Understand Kernel Learning (MB, SM, SM), pp. 540–548.
ICMLICML-2018-BlancR #adaptation
Adaptive Sampled Softmax with Kernel Based Sampling (GB, SR), pp. 589–598.
ICMLICML-2018-JiaoV #higher-order #permutation
The Weighted Kendall and High-order Kernels for Permutations (YJ, JPV), pp. 2319–2327.
ICMLICML-2018-KajiharaKYF #estimation #recursion
Kernel Recursive ABC: Point Estimation with Intractable Likelihood (TK, MK, KY, KF), pp. 2405–2414.
ICMLICML-2018-KumarSJ #metric #network
Trainable Calibration Measures For Neural Networks From Kernel Mean Embeddings (AK, SS, UJ), pp. 2810–2819.
ICMLICML-2018-MullerMI #matrix
Kernelized Synaptic Weight Matrices (LKM, JNPM, GI), pp. 3651–3660.
ICMLICML-2018-OglicG #learning
Learning in Reproducing Kernel Krein Spaces (DO, TG0), pp. 3856–3864.
ICMLICML-2018-OhGW #optimisation
BOCK : Bayesian Optimization with Cylindrical Kernels (CO, EG, MW), pp. 3865–3874.
ICMLICML-2018-SunZWZLG #composition #learning #process
Differentiable Compositional Kernel Learning for Gaussian Processes (SS, GZ, CW, WZ, JL, RBG), pp. 4835–4844.
ICMLICML-2018-XuSC #divide and conquer
Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data (GX, ZS, GC), pp. 5479–5487.
ICPRICPR-2018-0004YW #named
Spindle-Net: CNNs for Monocular Depth Inference with Dilation Kernel Method (LH0, MY, GW), pp. 2504–2509.
ICPRICPR-2018-BaiHA #analysis #correlation #recognition
Kernel Discriminant Correlation Analysis: Feature Level Fusion for Nonlinear Biometric Recognition (YB, MH, MAM), pp. 3198–3203.
ICPRICPR-2018-ChenWWK #approximate #classification #image #set
Riemannian kernel based Nyström method for approximate infinite-dimensional covariance descriptors with application to image set classification (KXC, XJW, RW, JK), pp. 651–656.
ICPRICPR-2018-CuiB00JH #graph #hybrid #learning #network
A Deep Hybrid Graph Kernel Through Deep Learning Networks (LC, LB0, LR0, YW0, YJ0, ERH), pp. 1030–1035.
ICPRICPR-2018-GaoSXL #classification #image #linear #set
Kernel Dual Linear Regression for Face Image Set Classification (XG, QS, HX, YL), pp. 1542–1547.
ICPRICPR-2018-GuoLLL #adaptation #identification #ranking
Density-Adaptive Kernel based Re-Ranking for Person Re-Identification (RPG, CGL, YL, JL), pp. 982–987.
ICPRICPR-2018-HuangXG #identification #incremental #null
Incremental Kernel Null Foley-Sammon Transform for Person Re-identification (XH, JX, GG), pp. 1683–1688.
ICPRICPR-2018-LiL18a #multi #online
An Online Kernel Selection Wrapper via Multi-Armed Bandit Model (JL, SL), pp. 1307–1312.
ICPRICPR-2018-MaGWW #named #symmetry
RotateConv: Making Asymmetric Convolutional Kernels Rotatable (JM, WG, WW0, LW0), pp. 55–60.
ICPRICPR-2018-MartinezPSLBP #functional #multi #personalisation #recognition
Multi-task multiple kernel machines for personalized pain recognition from functional near-infrared spectroscopy brain signals (DLM, KP, SCS, AJL, DB, RWP), pp. 2320–2325.
ICPRICPR-2018-XuDS #estimation #feature model
Semi-supervised Feature Selection by Mutual Information Based on Kernel Density Estimation (SX, JD, HS), pp. 818–823.
ICPRICPR-2018-XuZL18a #incremental #learning #linear #online
A Linear Incremental Nyström Method for Online Kernel Learning (SX, XZ, SL), pp. 2256–2261.
ICPRICPR-2018-ZhangJCXP #approach #graph #learning #network
Kernel-Weighted Graph Convolutional Network: A Deep Learning Approach for Traffic Forecasting (QZ, QJ, JC, SX, CP), pp. 1018–1023.
ICPRICPR-2018-ZhuMT #graph #multi #retrieval
Multi-Kernel Supervised Hashing with Graph Regularization for Cross-Modal Retrieval (MZ, HM, JT), pp. 2717–2722.
KDDKDD-2018-HongCL #learning
Disturbance Grassmann Kernels for Subspace-Based Learning (JH, HC, FL), pp. 1521–1530.
KDDKDD-2018-NguyenLNPW #big data #robust
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data (KN, TL, TDN, DQP, GIW), pp. 2003–2011.
KDDKDD-2018-TingZZ
Isolation Kernel and Its Effect on SVM (KMT, YZ, ZHZ), pp. 2329–2337.
ICMTICMT-2018-Voelter #design #evolution #functional #using
The Design, Evolution, and Use of KernelF — An Extensible and Embeddable Functional Language (MV), pp. 3–55.
PLDIPLDI-2018-HongSKRKPRS #analysis #gpu #optimisation #using
GPU code optimization using abstract kernel emulation and sensitivity analysis (CH, ASR, JK, PSR, SK, LNP, FR, PS), pp. 736–751.
ASEASE-2018-Diarra #automation #strict #towards
Towards automatic restrictification of CUDA kernel arguments (RD), pp. 928–931.
ASPLOSASPLOS-2018-AlglaveMMPS #concurrent #linux
Frightening Small Children and Disconcerting Grown-ups: Concurrency in the Linux Kernel (JA, LM, PEM, AP, ASS), pp. 405–418.
CASECASE-2018-CuiZFKM #policy #programming
Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control (YC, LZ, MF, HK, TM), pp. 304–309.
CGOCGO-2018-MaierCJ
Local memory-aware kernel perforation (DM, BC, BHHJ), pp. 278–287.
CSEETCSEET-2017-BallandCHKLMCRS #women
Girls Who . . . Do Scratch a First Round with the Essence Kernel (CB, NSC, LH, GK, AL, AM, LRLC, CR, MS, VD, CD, CF, CF, CH, AK, VR), pp. 251–255.
ICSMEICSME-2017-LiJZZ #fault #learning #multi #predict
Heterogeneous Defect Prediction Through Multiple Kernel Learning and Ensemble Learning (ZL0, XYJ, XZ, HZ0), pp. 91–102.
CIKMCIKM-2017-DangCWZC #classification #learning
Unsupervised Matrix-valued Kernel Learning For One Class Classification (SD, XC, YW0, JZ, FC0), pp. 2031–2034.
ICMLICML-2017-AvronKMMVZ #approximate #bound #fourier #random #statistics
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees (HA, MK, CM, CM, AV, AZ), pp. 253–262.
ICMLICML-2017-BriolOCCG #on the #problem
On the Sampling Problem for Kernel Quadrature (FXB, CJO, JC, WYC, MAG), pp. 586–595.
ICMLICML-2017-CalandrielloLV #adaptation #higher-order #online #optimisation #sketching
Second-Order Kernel Online Convex Optimization with Adaptive Sketching (DC, AL, MV), pp. 645–653.
ICMLICML-2017-CarriereCO #diagrams #persistent #slicing
Sliced Wasserstein Kernel for Persistence Diagrams (MC, MC, SO), pp. 664–673.
ICMLICML-2017-ChowdhuryG #multi #on the
On Kernelized Multi-armed Bandits (SRC, AG), pp. 844–853.
ICMLICML-2017-GorhamM #quality
Measuring Sample Quality with Kernels (JG, LWM), pp. 1292–1301.
ICMLICML-2017-HeLMWSYR
Kernelized Support Tensor Machines (LH0, CTL, GM, SW, LS, PSY, ABR), pp. 1442–1451.
ICMLICML-2017-Jiang17a #convergence #estimation
Uniform Convergence Rates for Kernel Density Estimation (HJ), pp. 1694–1703.
ICMLICML-2017-Jitkrittum0G #adaptation #independence
An Adaptive Test of Independence with Analytic Kernel Embeddings (WJ, ZS0, AG), pp. 1742–1751.
ICMLICML-2017-LeiJBJ #architecture #graph #sequence
Deriving Neural Architectures from Sequence and Graph Kernels (TL0, WJ, RB, TSJ), pp. 2024–2033.
ICMLICML-2017-LivniCG #infinity #learning #network
Learning Infinite Layer Networks Without the Kernel Trick (RL, DC, AG), pp. 2198–2207.
ICMLICML-2017-Lyu #approximate
Spherical Structured Feature Maps for Kernel Approximation (YL), pp. 2256–2264.
ICMLICML-2017-OglicG
Nyström Method with Kernel K-means++ Samples as Landmarks (DO, TG0), pp. 2652–2660.
ICMLICML-2017-SchlegelPCW #adaptation #online #using
Adapting Kernel Representations Online Using Submodular Maximization (MS, YP, JC, MW), pp. 3037–3046.
ICMLICML-2017-WangLJK #learning #optimisation
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning (ZW, CL, SJ, PK), pp. 3656–3664.
KDDKDD-2017-HsiehSD #distributed
Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines (CJH, SS, ISD), pp. 245–254.
KDDKDD-2017-Li #fourier #normalisation #random
Linearized GMM Kernels and Normalized Random Fourier Features (PL0), pp. 315–324.
KDDKDD-2017-WangAL #performance #random #re-engineering
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods (SW, CCA, HL0), pp. 485–494.
KDDKDD-2017-ZhengP
Coresets for Kernel Regression (YZ, JMP), pp. 645–654.
ASEASE-2017-CoppikSWS #fault #named #operating system
TrEKer: tracing error propagation in operating system kernels (NC, OS, SW0, NS), pp. 377–387.
ASEASE-2017-KjolstadCLKA #algebra #named
taco: a tool to generate tensor algebra kernels (FK, SC, DL, SK, SPA), pp. 943–948.
ESEC-FSEESEC-FSE-2017-SorensenED #algorithm #gpu #multi
Cooperative kernels: GPU multitasking for blocking algorithms (TS0, HE, AFD), pp. 431–441.
ESEC-FSEESEC-FSE-2017-WuY #android #framework #named
LaChouTi: kernel vulnerability responding framework for the fragmented Android devices (JW, MY), pp. 920–925.
ESEC-FSEESEC-FSE-2017-ZhouCMW #linux #maintenance #on the #scalability
On the scalability of Linux kernel maintainers' work (MZ, QC, AM, FW), pp. 27–37.
CGOCGO-2017-GongCZUK #execution #gpu #hardware #named #scheduling
TwinKernels: an execution model to improve GPU hardware scheduling at compile time (XG, ZC, AKZ, RU, DRK), pp. 39–49.
ICSTICST-2017-JeongLKKH #embedded #fault #framework #injection #linux #named
FIFA: A Kernel-Level Fault Injection Framework for ARM-Based Embedded Linux System (EJ, NL, JK, DK, SH), pp. 23–34.
VMCAIVMCAI-2017-MukherjeeKD #detection
Detecting All High-Level Dataraces in an RTOS Kernel (SM, AK, DD), pp. 405–423.
SCAMSCAM-2016-JimenezPT #case study #linux #modelling #predict
Vulnerability Prediction Models: A Case Study on the Linux Kernel (MJ, MP, YLT), pp. 1–10.
CIKMCIKM-2016-RoyGMJ #composition #estimation #feedback #using #word
Word Vector Compositionality based Relevance Feedback using Kernel Density Estimation (DR, DG, MM, GJFJ), pp. 1281–1290.
ECIRECIR-2016-CroceB #learning #scalability
Large-Scale Kernel-Based Language Learning Through the Ensemble Nystr đdoto o ¨ m Methods (DC, RB0), pp. 100–112.
ICMLICML-2016-ChoromanskiS #sublinear
Recycling Randomness with Structure for Sublinear time Kernel Expansions (KC, VS), pp. 2502–2510.
ICMLICML-2016-ChwialkowskiSG
A Kernel Test of Goodness of Fit (KC, HS, AG), pp. 2606–2615.
ICMLICML-2016-CutajarOCF #matrix
Preconditioning Kernel Matrices (KC, MAO, JPC, MF), pp. 2529–2538.
ICMLICML-2016-KusanoHF #data analysis #persistent
Persistence weighted Gaussian kernel for topological data analysis (GK, YH, KF), pp. 2004–2013.
ICMLICML-2016-LiJS #performance
Fast DPP Sampling for Nystrom with Application to Kernel Methods (CL, SJ, SS), pp. 2061–2070.
ICMLICML-2016-LiuLJ #testing
A Kernelized Stein Discrepancy for Goodness-of-fit Tests (QL, JDL, MIJ), pp. 276–284.
ICMLICML-2016-MitrovicST #approximate #named
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression (JM, DS, YWT), pp. 1482–1491.
ICMLICML-2016-PeyreCS #distance #matrix
Gromov-Wasserstein Averaging of Kernel and Distance Matrices (GP, MC, JS), pp. 2664–2672.
ICMLICML-2016-RamaswamyST #estimation
Mixture Proportion Estimation via Kernel Embeddings of Distributions (HGR, CS, AT), pp. 2052–2060.
ICPRICPR-2016-AwateDK #robust
Robust kernel principal nested spheres (SPA, MD, NK), pp. 402–407.
ICPRICPR-2016-Bai0CH #transitive
A transitive aligned Weisfeiler-Lehman subtree kernel (LB0, LR0, LC, ERH), pp. 396–401.
ICPRICPR-2016-BaiCEH
An edge-based matching kernel on commute-time spanning trees (LB0, LC, FE, ERH), pp. 2103–2108.
ICPRICPR-2016-BaiCWJ0H #classification #clustering #graph
Shape classification with a vertex clustering graph kernel (LB0, LC, YW0, XJ0, XB0, ERH), pp. 2634–2639.
ICPRICPR-2016-CavazzaZSM #recognition
Kernelized covariance for action recognition (JC, AZ, MSB, VM), pp. 408–413.
ICPRICPR-2016-GhoraiMC #image #statistics #using
Patch sparsity based image inpainting using local patch statistics and steering kernel descriptor (MG, SM, BC), pp. 781–786.
ICPRICPR-2016-HouP #clustering
A new density kernel in density peak based clustering (JH, MP), pp. 468–473.
ICPRICPR-2016-MaoFWH #identification #performance
Fast kernel SVM training via support vector identification (XM, ZF, OW, WH), pp. 1554–1559.
ICPRICPR-2016-PratesS #identification
Kernel Hierarchical PCA for person re-identification (RFdCP, WRS), pp. 2091–2096.
ICPRICPR-2016-RaytchevKTK #recognition #representation #using
Higher-level representation of local spatio-temporal features for human action recognition using Subspace Matching Kernels (BR, HK, TT, KK), pp. 3862–3867.
ICPRICPR-2016-RedkoB #learning
Kernel alignment for unsupervised transfer learning (IR, YB), pp. 525–530.
ICPRICPR-2016-SaikiaSSKG #analysis #learning #multi #using
Multiple kernel learning using data envelopment analysis and feature vector selection and projection (GS, SS, VVS, RDK, PG), pp. 520–524.
ICPRICPR-2016-YeLYZ #clustering #multi
Co-regularized kernel k-means for multi-view clustering (YY, XL, JY, EZ), pp. 1583–1588.
KDDKDD-2016-BalcanLSW0 #analysis #communication #component #distributed #performance
Communication Efficient Distributed Kernel Principal Component Analysis (MFB, YL, LS, DPW, BX0), pp. 725–734.
PLDIPLDI-2016-ChenWSLG #composition #towards #verification
Toward compositional verification of interruptible OS kernels and device drivers (HC0, X(W, ZS, JL, RG), pp. 431–447.
ASPLOSASPLOS-2016-ChangKH #lightweight #named #programming
DySel: Lightweight Dynamic Selection for Kernel-based Data-parallel Programming Model (LWC, HSK, WmWH), pp. 667–680.
ASPLOSASPLOS-2016-LinCLMHXS #design #implementation #scalability
Scalable Kernel TCP Design and Implementation for Short-Lived Connections (XL, YC0, XL, JM, JH, WX, YS), pp. 339–352.
CASECASE-2016-LiuS #learning #online #recognition #taxonomy
Online kernel dictionary learning for object recognition (HL0, FS), pp. 268–273.
CCCC-2016-HammacherSZH #concurrent #thread
Thread-level speculation with kernel support (CH, KS, AZ, SH), pp. 1–11.
CCCC-2016-MajetiMBS #architecture #automation #cpu #generative #gpu #layout
Automatic data layout generation and kernel mapping for CPU+GPU architectures (DM, KSM, RB, VS), pp. 240–250.
CAVCAV-2016-XuFFZZL #framework #verification
A Practical Verification Framework for Preemptive OS Kernels (FX, MF, XF, XZ, HZ, ZL), pp. 59–79.
SIGMODSIGMOD-2015-HeimelKM #estimation #modelling #multi #self
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation (MH, MK, VM), pp. 1477–1492.
ICALPICALP-v1-2015-GiannopoulouJLS #complexity
Uniform Kernelization Complexity of Hitting Forbidden Minors (ACG, BMPJ, DL, SS), pp. 629–641.
FMFM-2015-LiuH #analysis #android #case study #security
Case Study: Static Security Analysis of the Android Goldfish Kernel (TL, RH), pp. 589–592.
HCIDHM-EH-2015-BoZDYWF #hybrid #performance #recognition #using
Hybrid BFO-PSO and Kernel FCM for the Recognition of Pilot Performance Influenced by Simulator Movement Using Diffusion Maps (JB, YBZ, LD, BTY, QW, SF), pp. 239–247.
ICMLICML-2015-Bai0ZH #graph
An Aligned Subtree Kernel for Weighted Graphs (LB, LR, ZZ, ERH), pp. 30–39.
ICMLICML-2015-GiguereRLM #algorithm #predict #problem #string
Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction (SG, AR, FL, MM), pp. 2021–2029.
ICMLICML-2015-JiaoV #permutation
The Kendall and Mallows Kernels for Permutations (YJ, JPV), pp. 1935–1944.
ICMLICML-2015-WilsonN #process #scalability
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) (AGW, HN), pp. 1775–1784.
KDDKDD-2015-ChaoHZ #analysis
Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics (PC, QH, MZ), pp. 905–914.
KDDKDD-2015-MarchXTYB #approximate #robust
Robust Treecode Approximation for Kernel Machines (WBM, BX, ST, CDY, GB), pp. 775–784.
KDDKDD-2015-YanardagV #graph
Deep Graph Kernels (PY, SVNV), pp. 1365–1374.
KDDKDD-2015-ZhengP #fault #scalability
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data (YZ, JMP), pp. 1533–1542.
KDDKDD-2015-ZhouM #approach #predict
Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach (ZZ, DSM), pp. 2297–2303.
MLDMMLDM-2015-TanGZ #incremental #named
IKLTSA: An Incremental Kernel LTSA Method (CT, JG, SZ), pp. 70–83.
PLDIPLDI-2015-MendisBWKRPZA #domain-specific language #named
Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code (CM, JB, KW, SK, JRK, SP, QZ, SPA), pp. 391–402.
ESEC-FSEESEC-FSE-2015-DovgalyukDM #debugging
Don’t panic: reverse debugging of kernel drivers (PD, DD, VM), pp. 938–941.
ICSEICSE-v2-2015-Salgado #behaviour #cpu #gpu #interactive #profiling
Profiling Kernels Behavior to Improve CPU / GPU Interactions (RS), pp. 754–756.
SACSAC-2015-FerreiraMME #analysis #comparison #memory management
An experimental comparison analysis of kernel-level memory allocators (TBF, RM, AM, BEC), pp. 2054–2059.
ASPLOSASPLOS-2015-DautenhahnKDCA #architecture #operating system
Nested Kernel: An Operating System Architecture for Intra-Kernel Privilege Separation (ND, TK, WD, JC, VSA), pp. 191–206.
CGOCGO-2015-JiaoLHM #concurrent #energy #execution
Improving GPGPU energy-efficiency through concurrent kernel execution and DVFS (QJ, ML, HPH, TM), pp. 1–11.
DATEDATE-2015-GiefersPH
Accelerating arithmetic kernels with coherent attached FPGA coprocessors (HG, RP, CH), pp. 1072–1077.
HPDCHPDC-2015-HaleD #operating system #parallel
A Case for Transforming Parallel Runtimes Into Operating System Kernels (KCH, PAD), pp. 27–32.
HPDCHPDC-2015-OuyangKLP #lightweight #performance
Achieving Performance Isolation with Lightweight Co-Kernels (JO, BK, JRL, KTP), pp. 149–160.
HPDCHPDC-2015-WahibM #automation #gpu #scalability
Automated GPU Kernel Transformations in Large-Scale Production Stencil Applications (MW, NM), pp. 259–270.
LCTESLCTES-2015-0001HL #analysis #realtime
Cross-Kernel Control-Flow-Graph Analysis for Event-Driven Real-Time Systems (CD, MH, DL), p. 10.
PDPPDP-2015-GuerreiroIRT #energy #multi #optimisation #performance
Multi-kernel Auto-Tuning on GPUs: Performance and Energy-Aware Optimization (JG, AI, NR, PT), pp. 438–445.
PDPPDP-2015-KonstantinidisC #bound #gpu #memory management #performance
A Practical Performance Model for Compute and Memory Bound GPU Kernels (EK, YC), pp. 651–658.
PPoPPPPoPP-2015-AshariTBRCKS #machine learning #on the #optimisation
On optimizing machine learning workloads via kernel fusion (AA, ST, MB, BR, KC, JK, PS), pp. 173–182.
MSRMSR-2014-PassosC #dataset #feature model #linux
A dataset of feature additions and feature removals from the Linux kernel (LTP, KC), pp. 376–379.
CIAACIAA-2014-Roche-LimaDF #automaton
Pairwise Rational Kernels Obtained by Automaton Operations (ARL, MD, BF), pp. 332–345.
LATALATA-2014-BellaouarCZ #performance #sequence #string
Efficient List-Based Computation of the String Subsequence Kernel (SB, HC, DZ), pp. 138–148.
CSCWCSCW-2014-Ribes14a #framework #research
The kernel of a research infrastructure (DR), pp. 574–587.
CIKMCIKM-2014-AnnesiCB #composition #semantics
Semantic Compositionality in Tree Kernels (PA, DC, RB), pp. 1029–1038.
ECIRECIR-2014-FiliceCCB #effectiveness #learning #online
Effective Kernelized Online Learning in Language Processing Tasks (SF, GC, DC, RB), pp. 347–358.
ICMLICML-c1-2014-HsiehSD #divide and conquer
A Divide-and-Conquer Solver for Kernel Support Vector Machines (CJH, SS, ISD), pp. 566–574.
ICMLICML-c1-2014-IyerNS #bound #convergence #estimation
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection (AI, SN, SS), pp. 530–538.
ICMLICML-c1-2014-LiuJL #approximate #performance #using
Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function (YL, SJ, SL), pp. 324–332.
ICMLICML-c1-2014-MuandetFSGS #estimation
Kernel Mean Estimation and Stein Effect (KM, KF, BKS, AG, BS), pp. 10–18.
ICMLICML-c1-2014-RamdasP
Margins, Kernels and Non-linear Smoothed Perceptrons (AR, JP), pp. 244–252.
ICMLICML-c1-2014-SiHD #approximate #memory management #performance
Memory Efficient Kernel Approximation (SS, CJH, ISD), pp. 701–709.
ICMLICML-c1-2014-YangSAM #invariant #monte carlo
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels (JY, VS, HA, MWM), pp. 485–493.
ICMLICML-c2-2014-AffandiFAT #learning #parametricity #process
Learning the Parameters of Determinantal Point Process Kernels (RHA, EBF, RPA, BT), pp. 1224–1232.
ICMLICML-c2-2014-ChwialkowskiG #independence #process #random
A Kernel Independence Test for Random Processes (KC, AG), pp. 1422–1430.
ICMLICML-c2-2014-GiesenLW #performance #robust
Robust and Efficient Kernel Hyperparameter Paths with Guarantees (JG, SL, PW), pp. 1296–1304.
ICMLICML-c2-2014-JawanpuriaVN #feature model #learning #multi #on the
On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection (PJ, MV, JSN), pp. 118–126.
ICMLICML-c2-2014-JohanssonJDB #geometry #graph #using
Global graph kernels using geometric embeddings (FJ, VJ, DPD, CB), pp. 694–702.
ICMLICML-c2-2014-SejdinovicSGAG #adaptation
Kernel Adaptive Metropolis-Hastings (DS, HS, MLG, CA, AG), pp. 1665–1673.
ICPRICPR-2014-AzizWH #graph #using
Graph Characterization Using Wave Kernel Trace (FA, RCW, ERH), pp. 3822–3827.
ICPRICPR-2014-BaiBH #graph
An Attributed Graph Kernel from the Jensen-Shannon Divergence (LB, HB, ERH), pp. 88–93.
ICPRICPR-2014-BaiRH #morphism #testing
A Hypergraph Kernel from Isomorphism Tests (LB, PR, ERH), pp. 3880–3885.
ICPRICPR-2014-BauckhageM #analysis #clustering #web
Kernel Archetypal Analysis for Clustering Web Search Frequency Time Series (CB, KM), pp. 1544–1549.
ICPRICPR-2014-CaoHS #approach #classification #learning #multi
Optimization-Based Extreme Learning Machine with Multi-kernel Learning Approach for Classification (LlC, WbH, FS), pp. 3564–3569.
ICPRICPR-2014-Cardenas-PenaOCAC #3d #clustering #representation
A Kernel-Based Representation to Support 3D MRI Unsupervised Clustering (DCP, MOA, AECO, AMÁM, GCD), pp. 3203–3208.
ICPRICPR-2014-DamoulasHBGA #string
String Kernels for Complex Time-Series: Counting Targets from Sensed Movement (TD, JH, RB, CPG, AA), pp. 4429–4434.
ICPRICPR-2014-GaurHC #design #distance #image #multi
Design of Multi-kernel Distance Based Hashing with Multiple Objectives for Image Indexing (VG, EH, SC), pp. 2637–2642.
ICPRICPR-2014-GauzereBV #encoding #graph
Graph Kernel Encoding Substituents’ Relative Positioning (BG, LB, DV), pp. 637–642.
ICPRICPR-2014-GavriilidisT #classification #random #using
Random Walk Kernel Applications to Classification Using Support Vector Machines (VG, AT), pp. 3898–3903.
ICPRICPR-2014-GiordanoPS #estimation #modelling #using
Kernel Density Estimation Using Joint Spatial-Color-Depth Data for Background Modeling (DG, SP, CS), pp. 4388–4393.
ICPRICPR-2014-GrenierBV #graph
A Graph Kernel Incorporating Molecule’s Stereisomerism Information (PAG, LB, DV), pp. 631–636.
ICPRICPR-2014-GuoZLCZ #clustering #learning #multi
Multiple Kernel Learning Based Multi-view Spectral Clustering (DG, JZ, XL, YC, CZ), pp. 3774–3779.
ICPRICPR-2014-MarteauGR #gesture #performance #recognition
Down-sampling Coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures (PFM, SG, CR), pp. 363–368.
ICPRICPR-2014-NocetiO #classification #graph #process
A Spectral Graph Kernel and Its Application to Collective Activities Classification (NN, FO), pp. 3892–3897.
ICPRICPR-2014-OHarneyMRCSCBF #learning #multi #pseudo
Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data (ADO, AM, KR, KC, ABS, AC, CB, MF), pp. 3185–3190.
ICPRICPR-2014-OuyedA #classification
Feature Relevance for Kernel Logistic Regression and Application to Action Classification (OO, MSA), pp. 1325–1329.
ICPRICPR-2014-PerinaKB #array #classification #using
Expression Microarray Data Classification Using Counting Grids and Fisher Kernel (AP, MK, MB), pp. 1770–1775.
ICPRICPR-2014-PistocchiCBFC #3d #classification #detection
Kernelized Structural Classification for 3D Dogs Body Parts Detection (SP, SC, SB, NF, RC), pp. 1993–1998.
ICPRICPR-2014-RozzaMP #graph #learning #novel
A Novel Graph-Based Fisher Kernel Method for Semi-supervised Learning (AR, MM, AP), pp. 3786–3791.
ICPRICPR-2014-Sahbi #image
Network-Dependent Image Annotation Based on Explicit Context-Dependent Kernel Maps (HS), pp. 625–630.
ICPRICPR-2014-ScheltenR #estimation #image #locality #parametricity
Localized Image Blur Removal through Non-parametric Kernel Estimation (KS, SR), pp. 702–707.
KDDKDD-2014-KlosterG #community #detection
Heat kernel based community detection (KK, DFG), pp. 1386–1395.
KDDKDD-2014-Kushnir #adaptation #learning
Active-transductive learning with label-adapted kernels (DK), pp. 462–471.
KDDKDD-2014-LichmanS #modelling
Modeling human location data with mixtures of kernel densities (ML, PS), pp. 35–44.
KDDKDD-2014-SahooHL #multi #online
Online multiple kernel regression (DS, SCHH, BL), pp. 293–302.
KDIRKDIR-2014-SatoNS #classification #using
A Simple Classification Method for Class Imbalanced Data using the Kernel Mean (YS, KN, AS), pp. 327–334.
SEKESEKE-2014-SatapathyPR #agile #approach #estimation #using
Story Point Approach based Agile Software Effort Estimation using Various SVR Kernel Methods (SMS, AP, SKR), pp. 304–307.
SIGIRSIGIR-2014-AnilSS #evolution #modelling #network #social #using
Modeling evolution of a social network using temporalgraph kernels (AA, NS, SRS), pp. 1051–1054.
OOPSLAOOPSLA-2014-MisailovicCAQR #approximate #named #optimisation
Chisel: reliability- and accuracy-aware optimization of approximate computational kernels (SM, MC, SA, ZQ, MCR), pp. 309–328.
AdaEuropeAdaEurope-2014-SaezC #predict #realtime
Integrated Schedulers for a Predictable Interrupt Management on Real-Time Kernels (SS, AC), pp. 134–148.
ASEASE-2014-AbalBW #analysis #debugging #linux #variability
42 variability bugs in the linux kernel: a qualitative analysis (IA, CB, AW), pp. 421–432.
SACSAC-2014-JeongLCHP #android #approach #behaviour #monitoring
A kernel-based monitoring approach for analyzing malicious behavior on Android (YJ, HtL, SC, SH, MP), pp. 1737–1738.
SACSAC-2014-OliveiraNWB #approach #named
Ianus: secure and holistic coexistence with kernel extensions — a immune system-inspired approach (DO, JN, NW, MB), pp. 1672–1679.
SACSAC-2014-OliveiraO #analysis #linux
Mapping of the synchronization mechanisms of the Linux kernel to the response-time analysis model (DBdO, RSdO), pp. 1543–1544.
SACSAC-2014-ParkKC #framework #memory management #online #platform #using
Cooperative kernel: online memory test platform using inter-kernel context switch and memory isolation (HP, DK, JC), pp. 1517–1522.
CGOCGO-2014-PanditG #execution #multi #source code
Fluidic Kernels: Cooperative Execution of OpenCL Programs on Multiple Heterogeneous Devices (PP, RG), p. 273.
DATEDATE-2014-NelsonNMKG #composition #named #predict #realtime
CoMik: A predictable and cycle-accurately composable real-time microkernel (AN, ABN, AMM, MK, KG), pp. 1–4.
OSDIOSDI-2014-0001RB #concurrent #debugging #named
SKI: Exposing Kernel Concurrency Bugs through Systematic Schedule Exploration (PF, RR, BBB), pp. 415–431.
OSDIOSDI-2014-WangLZCT #framework #interpreter #named
Jitk: A Trustworthy In-Kernel Interpreter Infrastructure (XW, DL, NZ, AC, ZT), pp. 33–47.
OSDIOSDI-2014-ZellwegerGKR #operating system
Decoupling Cores, Kernels, and Operating Systems (GZ, SG, KK, TR), pp. 17–31.
CAVCAV-2014-BardsleyBCCDDKLQ #gpu #verification
Engineering a Static Verification Tool for GPU Kernels (EB, AB, NC, PC, PD, AFD, JK, DL, SQ), pp. 226–242.
ICDARICDAR-2013-MondalRRP #locality #performance #retrieval #word
A Fast Word Retrieval Technique Based on Kernelized Locality Sensitive Hashing (TM, NR, JYR, UP), pp. 1195–1199.
ICDARICDAR-2013-ZhangT #documentation #keyword
Segmentation-Free Keyword Spotting for Handwritten Documents Based on Heat Kernel Signature (XZ, CLT), pp. 827–831.
SIGMODSIGMOD-2013-ZhengJPL #performance #quality #scalability
Quality and efficiency for kernel density estimates in large data (YZ, JJ, JMP, FL), pp. 433–444.
MSRMSR-2013-JiangAG #case study #how #linux #performance
Will my patch make it? and how fast?: case study on the Linux kernel (YJ, BA, DMG), pp. 101–110.
ICALPICALP-v1-2013-0002LPRRSS #algorithm #linear
Linear Kernels and Single-Exponential Algorithms via Protrusion Decompositions (EJK, AL, CP, FR, PR, IS, SS), pp. 613–624.
HCIHCI-III-2013-XuGC #classification #representation
Kernel Based Weighted Group Sparse Representation Classifier (BX, PG, CLPC), pp. 236–245.
HCIHCI-III-2013-YangWC #clustering #fuzzy #image #segmentation #similarity
Kernel Fuzzy Similarity Measure-Based Spectral Clustering for Image Segmentation (YY, YW, YmC), pp. 246–253.
CIKMCIKM-2013-ChanYTDZW #categorisation #classification #community #topic
Community question topic categorization via hierarchical kernelized classification (WC, WY, JT, JD, XZ, WW), pp. 959–968.
CIKMCIKM-2013-HermanssonKJJD #ambiguity #graph #using
Entity disambiguation in anonymized graphs using graph kernels (LH, TK, FJ, VJ, DPD), pp. 1037–1046.
ICMLICML-c1-2013-AfkanpourGSB #algorithm #learning #multi #random #scalability
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning (AA, AG, CS, MB), pp. 374–382.
ICMLICML-c1-2013-KadriGP #approach #learning
A Generalized Kernel Approach to Structured Output Learning (HK, MG, PP), pp. 471–479.
ICMLICML-c1-2013-Shin #design #future of
A New Frontier of Kernel Design for Structured Data (KS), pp. 401–409.
ICMLICML-c2-2013-ChangKKZ #analysis #canonical #correlation #independence
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment (BC, UK, RK, JZ), pp. 316–324.
ICMLICML-c3-2013-0002T #learning
Differentially Private Learning with Kernels (PJ, AT), pp. 118–126.
ICMLICML-c3-2013-CortesMR #classification #multi
Multi-Class Classification with Maximum Margin Multiple Kernel (CC, MM, AR), pp. 46–54.
ICMLICML-c3-2013-DuvenaudLGTG #composition #parametricity
Structure Discovery in Nonparametric Regression through Compositional Kernel Search (DKD, JRL, RBG, JBT, ZG), pp. 1166–1174.
ICMLICML-c3-2013-GonenKK #matrix
Kernelized Bayesian Matrix Factorization (MG, SAK, SK), pp. 864–872.
ICMLICML-c3-2013-JoseGAV #learning #performance #predict
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction (CJ, PG, PA, MV), pp. 486–494.
ICMLICML-c3-2013-WilsonA #process
Gaussian Process Kernels for Pattern Discovery and Extrapolation (AGW, RPA), pp. 1067–1075.
ICMLICML-c3-2013-ZhangYJLH #bound #learning #online
Online Kernel Learning with a Near Optimal Sparsity Bound (LZ, JY, RJ, ML, XH), pp. 621–629.
ICMLICML-c3-2013-ZhangZWKYM
Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels (KZ, VWZ, QW, JTYK, QY, IM), pp. 388–395.
ICMLICML-c3-2013-ZhouZS #learning #multi #process
Learning Triggering Kernels for Multi-dimensional Hawkes Processes (KZ, HZ, LS), pp. 1301–1309.
KDDKDD-2013-ChenTTY #analysis #modelling #performance
Model-based kernel for efficient time series analysis (HC, FT, PT, XY), pp. 392–400.
KDDKDD-2013-PhamP #performance #polynomial #scalability
Fast and scalable polynomial kernels via explicit feature maps (NP, RP), pp. 239–247.
MLDMMLDM-2013-OnoderaS
The Gapped Spectrum Kernel for Support Vector Machines (TO, TS), pp. 1–15.
SIGIRSIGIR-2013-Moschitti #learning #rank #semantics
Kernel-based learning to rank with syntactic and semantic structures (AM), p. 1128.
SPLCSPLC-2013-PassosGTCWB #case study #linux #modelling #variability
Coevolution of variability models and related artifacts: a case study from the Linux kernel (LTP, JG, LT, KC, AW, PB), pp. 91–100.
OOPSLAOOPSLA-2013-ChongDKKQ #abstraction #analysis #gpu #invariant
Barrier invariants: a shared state abstraction for the analysis of data-dependent GPU kernels (NC, AFD, PHJK, JK, SQ), pp. 605–622.
PLDIPLDI-2013-SewellMK #validation
Translation validation for a verified OS kernel (TALS, MOM, GK), pp. 471–482.
ICSEICSE-2013-XingXJ #benchmark #feature model #metric #research #scalability
A large scale Linux-kernel based benchmark for feature location research (ZX, YX, SJ), pp. 1311–1314.
SACSAC-2013-BaldovinGMV
Kernel-level time composability for avionics applications (AB, AG, EM, TV), pp. 1552–1554.
SACSAC-2013-SeelandKP #graph #learning
Model selection based product kernel learning for regression on graphs (MS, SK, BP), pp. 136–143.
SACSAC-2013-ShihL #manycore #named
nuKernel: MicroKernel for multi-core DSP SoCs with load sharing and priority interrupts (CSS, HYL), pp. 1525–1532.
ASPLOSASPLOS-2013-MadhavapeddyMRSSGSHC #library #named #operating system
Unikernels: library operating systems for the cloud (AM, RM, CR, DJS, BS, TG, SS, SH, JC), pp. 461–472.
ASPLOSASPLOS-2013-PaiTG #concurrent
Improving GPGPU concurrency with elastic kernels (SP, MJT, RG), pp. 407–418.
DACDAC-2013-LinLM #analysis #hybrid #reachability #verification
Verification of digitally-intensive analog circuits via kernel ridge regression and hybrid reachability analysis (HL, PL, CJM), p. 6.
DACDAC-2013-PapakonstantinouCHCL #migration
Throughput-oriented kernel porting onto FPGAs (AP, DC, WmWH, JC, YL), p. 10.
DACDAC-2013-WangK #control flow #detection #hardware #named #performance #using
NumChecker: detecting kernel control-flow modifying rootkits by using hardware performance counters (XW, RK), p. 7.
DATEDATE-2013-AliasDP #optimisation #synthesis
Optimizing remote accesses for offloaded kernels: application to high-level synthesis for FPGA (CA, AD, AP), pp. 575–580.
DATEDATE-2013-ChabrolRDJHOZ #realtime
Time- and angle-triggered real-time kernel (DC, DR, VD, MJ, MAH, PO, GZ), pp. 1060–1062.
PDPPDP-2013-FangVSS #api #memory management #named
ELMO: A User-Friendly API to Enable Local Memory in OpenCL Kernels (JF, ALV, JS, HJS), pp. 375–383.
PDPPDP-2013-MichailidisM #estimation #manycore #modelling #parallel #programming
Parallel Computing of Kernel Density Estimation with Different Multi-core Programming Models (PDM, KGM), pp. 77–85.
SOSPSOSP-2013-ElphinstoneH #question #what
From L3 to seL4 what have we learnt in 20 years of L4 microkernels? (KE, GH), pp. 133–150.
SOSPSOSP-2013-KediaB #performance
Fast dynamic binary translation for the kernel (PK, SB), pp. 101–115.
SOSPSOSP-2013-NikolaevB #named #operating system
VirtuOS: an operating system with kernel virtualization (RN, GB), pp. 116–132.
ESOPESOP-2013-CollingbourneDKQ #analysis #gpu #semantics #verification
Interleaving and Lock-Step Semantics for Analysis and Verification of GPU Kernels (PC, AFD, JK, SQ), pp. 270–289.
CSMRCSMR-2012-MurtazaSHC #comparison #identification #on the
On the Comparison of User Space and Kernel Space Traces in Identification of Software Anomalies (SSM, AS, AHL, MC), pp. 127–136.
ICPCICPC-2012-JbaraMF #linux
High-MCC functions in the Linux kernel (AJ, AM, DGF), pp. 83–92.
ICSMEICSM-2012-SuvorovNHZA #case study #empirical #linux
An empirical study of build system migrations in practice: Case studies on KDE and the Linux kernel (RS, MN, AEH, YZ, BA), pp. 160–169.
CIAACIAA-2012-AmarniL #sequence
Factor and Subsequence Kernels and Signatures of Rational Languages (AA, SL), pp. 313–320.
CIKMCIKM-2012-ComarLSNT #detection #linear
Weighted linear kernel with tree transformed features for malware detection (PMC, LL, SS, AN, PNT), pp. 2287–2290.
ICMLICML-2012-BalakrishnanPL #functional
Sparse Additive Functional and Kernel CCA (SB, KP, JDL), p. 97.
ICMLICML-2012-CotterSS #probability
The Kernelized Stochastic Batch Perceptron (AC, SSS, NS), p. 98.
ICMLICML-2012-Gonen #learning #multi #performance
Bayesian Efficient Multiple Kernel Learning (MG), p. 17.
ICMLICML-2012-HoiWZJW #algorithm #bound #learning #online #performance #scalability
Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning (SCHH, JW, PZ, RJ, PW), p. 141.
ICMLICML-2012-KimuraK #performance
Fast Computation of Subpath Kernel for Trees (DK, HK), p. 81.
ICMLICML-2012-KriegeM #graph
Subgraph Matching Kernels for Attributed Graphs (NK, PM), p. 42.
ICMLICML-2012-KumarNKD #classification #framework #learning #multi
A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICMLICML-2012-PoczosGS #dependence #metric
Copula-based Kernel Dependency Measures (BP, ZG, JGS), p. 213.
ICMLICML-2012-SejdinovicGSF #testing #using
Hypothesis testing using pairwise distances and associated kernels (DS, AG, BKS, KF), p. 104.
ICMLICML-2012-SunGS #on the #online #taxonomy
On the Size of the Online Kernel Sparsification Dictionary (YS, FJG, JS), p. 79.
ICMLICML-2012-YangMJZZ #learning #multi #probability #programming
Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.
ICMLICML-2012-YuS #analysis
Analysis of Kernel Mean Matching under Covariate Shift (YY, CS), p. 150.
ICMLICML-2012-ZanzottoD #distributed
Distributed Tree Kernels (FMZ, LD), p. 20.
ICPRICPR-2012-0007B #classification #feature model #image #multi
Multiple local kernel integrated feature selection for image classification (YS, BB), pp. 2230–2233.
ICPRICPR-2012-AtmosukartoGA #recognition #representation
Trajectory-based Fisher kernel representation for action recognition in videos (IA, BG, NA), pp. 3333–3336.
ICPRICPR-2012-BaiHR #graph #using
Jensen-Shannon graph kernel using information functionals (LB, ERH, PR), pp. 2877–2880.
ICPRICPR-2012-BanerjeeN #learning #multi #process #recognition #using
Pose based activity recognition using Multiple Kernel learning (PB, RN), pp. 445–448.
ICPRICPR-2012-BougleuxDBGM #combinator #similarity
Shape similarity based on combinatorial maps and a tree pattern kernel (SB, FXD, LB, BG, MM), pp. 1602–1605.
ICPRICPR-2012-ChandraJ #sequence #video
Partial Least Squares kernel for computing similarities between video sequences (SC, CVJ), pp. 513–516.
ICPRICPR-2012-ChengYLL #categorisation #nearest neighbour
A Pyramid Nearest Neighbor Search Kernel for object categorization (HC, RY, ZL, YL), pp. 2809–2812.
ICPRICPR-2012-ChoKKA #detection
Bilateral kernel-based Region Detector (WC, SYK, AK, MAA), pp. 750–753.
ICPRICPR-2012-DuttaGLBP #documentation #graph #random #visual notation
Combination of product graph and random walk kernel for symbol spotting in graphical documents (AD, JG, JL, HB, UP), pp. 1663–1666.
ICPRICPR-2012-El-GaalyT #multi #recognition #using
RGBD object pose recognition using local-global multi-kernel regression (TEG, MT), pp. 2468–2471.
ICPRICPR-2012-FausserS #clustering #dataset #scalability
Clustering large datasets with kernel methods (SF, FS), pp. 501–504.
ICPRICPR-2012-FreytagFRD #performance #process #segmentation #semantics
Efficient semantic segmentation with Gaussian processes and histogram intersection kernels (AF, BF, ER, JD), pp. 3313–3316.
ICPRICPR-2012-GaoM #analysis #canonical #correlation #detection #multi #using
Multi-modality movie scene detection using Kernel Canonical Correlation Analysis (GG, HM), pp. 3074–3077.
ICPRICPR-2012-GauzereBVB #graph
Graph kernels based on relevant patterns and cycle information for chemoinformatics (BG, LB, DV, MB), pp. 1775–1778.
ICPRICPR-2012-GuQFLW #image #multi
Image super-resolution based on multikernel regression (YG, YQ, TZF, CL, HW), pp. 2071–2074.
ICPRICPR-2012-Havens #approximate #streaming
Approximation of kernel k-means for streaming data (TCH), pp. 509–512.
ICPRICPR-2012-HinoO #learning #multi
An improved entropy-based multiple kernel learning (HH, TO), pp. 1189–1192.
ICPRICPR-2012-HuangLC #clustering #feature model #multi #self
Cluster-dependent feature selection by multiple kernel self-organizing map (KCH, YYL, JZC), pp. 589–592.
ICPRICPR-2012-IsmaeilAO #evaluation #exponential
Bilateral filter evaluation based on exponential kernels (KAI, DA, BEO), pp. 258–261.
ICPRICPR-2012-KangLXP #classification #representation
Kernel Homotopy based sparse representation for object classification (CK, SL, SX, CP), pp. 1479–1482.
ICPRICPR-2012-LiCHWM #3d #learning #multi #recognition
3D facial expression recognition via multiple kernel learning of Multi-Scale Local Normal Patterns (HL, LC, DH, YW, JMM), pp. 2577–2580.
ICPRICPR-2012-LiuF #analysis #multi
Multiple kernel discriminant analysis (XZL, GCF), pp. 1691–1694.
ICPRICPR-2012-LiuW12a #feature model
Unsupervised discriminative feature selection in a kernel space via L2, 1-norm minimization (YL, YW), pp. 1205–1208.
ICPRICPR-2012-LuLY #adaptation #classification #learning
Adaptive kernel learning based on centered alignment for hierarchical classification (YL, JL, JY), pp. 569–572.
ICPRICPR-2012-PanLS #learning
Learning kernels from labels with ideal regularization (BP, JHL, LS), pp. 505–508.
ICPRICPR-2012-San-BiagioUCCCM #approach #classification #learning #multi
A multiple kernel learning approach to multi-modal pedestrian classification (MSB, AU, MC, MC, UC, VM), pp. 2412–2415.
ICPRICPR-2012-SchleifZGH #approximate #clustering #performance #relational
Fast approximated relational and kernel clustering (FMS, XZ, AG, BH), pp. 1229–1232.
ICPRICPR-2012-TiribuziPVR #detection #framework #learning #multi
A Multiple Kernel Learning framework for detecting altered fingerprints (MT, MP, PV, ER), pp. 3402–3405.
ICPRICPR-2012-WangL #estimation #image #robust
Robust kernel estimation for single image blind deconvolution (FW, YL), pp. 481–484.
ICPRICPR-2012-XueCH #classification #constraints
Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data (HX, SC, JH), pp. 497–500.
ICPRICPR-2012-ZhangSSLWTBC #category theory #image
Spatial graphlet matching kernel for recognizing aerial image categories (LZ, MS, LS, XL, YW, DT, JB, CC), pp. 2813–2816.
ICPRICPR-2012-ZhangWXZL #recognition
Contextual Fisher kernels for human action recognition (ZZ, CW, BX, WZ, SL), pp. 437–440.
ICPRICPR-2012-ZhengZ #recognition #speech
Speech emotion recognition based on kernel reduced-rank regression (WZ, XZ), pp. 1972–1976.
ICPRICPR-2012-ZhuW #gesture #recognition #using
Single-frame hand gesture recognition using color and depth kernel descriptors (XZ, KYKW), pp. 2989–2992.
ICPRICPR-2012-ZhuXWF #recognition #representation
Kernel based sparse representation for face recognition (QZ, YX, JW, ZF), pp. 1703–1706.
KDDKDD-2012-JainVV #learning #multi #named
SPF-GMKL: generalized multiple kernel learning with a million kernels (AJ, SVNV, MV), pp. 750–758.
KDDKDD-2012-KuksaP #evaluation #performance #scalability #sequence
Efficient evaluation of large sequence kernels (PPK, VP), pp. 759–767.
KDDKDD-2012-SeelandKK #clustering #graph #learning
A structural cluster kernel for learning on graphs (MS, AK, SK), pp. 516–524.
SEKESEKE-2012-VicenteDMM #comprehension #execution #operating system
Improving Program Comprehension in Operating System Kernels with Execution Trace Information (EV, GD, RM, MdAM), pp. 174–179.
SIGIRSIGIR-2012-XiaWHJ #image #multi #retrieval #scalability
Boosting multi-kernel locality-sensitive hashing for scalable image retrieval (HX, PW, SCHH, RJ), pp. 55–64.
OOPSLAOOPSLA-2012-BettsCDQT #gpu #named #verification
GPUVerify: a verifier for GPU kernels (AB, NC, AFD, SQ, PT), pp. 113–132.
PLDIPLDI-2012-LeungGAGJL #gpu #verification
Verifying GPU kernels by test amplification (AL, MG, YA, RG, RJ, SL), pp. 383–394.
ASEASE-2012-BissyandeRLM #automation #debugging #generative #interface #linux #named
Diagnosys: automatic generation of a debugging interface to the Linux kernel (TFB, LR, JLL, GM), pp. 60–69.
ASEASE-2012-IbrahimGHA #ambiguity #analysis #operating system #points-to #using
Supporting operating system kernel data disambiguation using points-to analysis (ASI, JG, JHHH, MA), pp. 234–237.
SACSAC-2012-FahmyRJ #implementation #interface #linux #programming #realtime #scheduling #thread
Implementing distributable real-time threads in the Linux kernel: programming interface and scheduling support (SFF, BR, EDJ), pp. 1771–1778.
SACSAC-2012-HanJ #clustering #linux
Kernel-level ARINC 653 partitioning for Linux (SH, HWJ), pp. 1632–1637.
SACSAC-2012-HuaS #lightweight #memory management #named
Barrier: a lightweight hypervisor for protecting kernel integrity via memory isolation (JH, KS), pp. 1470–1477.
SACSAC-2012-MavrogiannopoulosTP #encryption #framework #linux
A linux kernel cryptographic framework: decoupling cryptographic keys from applications (NM, MT, BP), pp. 1435–1442.
SACSAC-2012-MenorPB #predict #probability #using
Probabilistic prediction of protein phosphorylation sites using kernel machines (MM, GP, KB), pp. 1393–1398.
ASPLOSASPLOS-2012-FeinerBG
Comprehensive kernel instrumentation via dynamic binary translation (PF, ADB, AG), pp. 135–146.
CASECASE-2012-ZhuSZZ #assessment #multi
A novelty degradation assessment method for equipment based on multi-kernel SVDD (YZ, YS, XZ, YZ), pp. 753–756.
CCCC-2012-UnkuleSQ #automation #gpu #locality #thread
Automatic Restructuring of GPU Kernels for Exploiting Inter-thread Data Locality (SU, CS, AQ), pp. 21–40.
CGOCGO-2012-KerrDY #compilation
Dynamic compilation of data-parallel kernels for vector processors (AK, GFD, SY), pp. 23–32.
DATEDATE-2012-Mancini #memory management #synthesis
Enhancing non-linear kernels by an optimized memory hierarchy in a High Level Synthesis flow (SM, FR), pp. 1130–1133.
PDPPDP-2012-CastilloFMQR #algebra #analysis #energy #linear #message passing
Analysis of Strategies to Save Energy for Message-Passing Dense Linear Algebra Kernels (MC, JCF, RM, ESQO, VR), pp. 346–352.
PPoPPPPoPP-2012-AliasDP #optimisation #synthesis
Optimizing remote accesses for offloaded kernels: application to high-level synthesis for FPGA (CA, AD, AP), pp. 285–286.
PPoPPPPoPP-2012-KimH #code generation #performance
Efficient SIMD code generation for irregular kernels (SK, HH), pp. 55–64.
PPoPPPPoPP-2012-TaoBB #development #gpu #scalability #using
Using GPU’s to accelerate stencil-based computation kernels for the development of large scale scientific applications on heterogeneous systems (JT, MB, SRB), pp. 287–288.
WCREWCRE-2011-Raber #debugging #profiling
Stealthy Profiling and Debugging of Malware Trampolining from User to Kernel Space (JR), pp. 431–432.
WCREWCRE-2011-WangLXJ #empirical #information retrieval #linux #locality #using
Concern Localization using Information Retrieval: An Empirical Study on Linux Kernel (SW, DL, ZX, LJ), pp. 92–96.
CIAACIAA-J-2010-AllauzenCM11 #algorithm #coordination
A Dual Coordinate Descent Algorithm for SVMs Combined with Rational Kernels (CA, CC, MM), pp. 1761–1779.
ICALPICALP-v1-2011-BodlaenderJK #analysis #combinator #preprocessor
Preprocessing for Treewidth: A Combinatorial Analysis through Kernelization (HLB, BMPJ, SK), pp. 437–448.
SFMSFM-2011-Moschitti #automation #learning #modelling
Kernel-Based Machines for Abstract and Easy Modeling of Automatic Learning (AM), pp. 458–503.
ICFPICFP-2011-GotsmanY #composition #verification
Modular verification of preemptive OS kernels (AG, HY), pp. 404–417.
CIKMCIKM-2011-CroceMB #dependence #semantics
Semantic convolution kernels over dependency trees: smoothed partial tree kernel (DC, AM, RB), pp. 2013–2016.
CIKMCIKM-2011-LiuLH #bound #fault #learning
Learning kernels with upper bounds of leave-one-out error (YL, SL, YH), pp. 2205–2208.
CIKMCIKM-2011-PimentelCS #clustering #data-driven #database #metric
A partitioning method for symbolic interval data based on kernelized metric (BAP, AFBFdC, RMCRdS), pp. 2189–2192.
CIKMCIKM-2011-XuSPZ #named #performance
TAKES: a fast method to select features in the kernel space (YX, FS, WP, JZ), pp. 683–692.
ICMLICML-2011-BrouarddS #predict
Semi-supervised Penalized Output Kernel Regression for Link Prediction (CB, FdB, MS), pp. 593–600.
ICMLICML-2011-CossalterYZ #adaptation #approximate #predict #scalability
Adaptive Kernel Approximation for Large-Scale Non-Linear SVM Prediction (MC, RY, LZ), pp. 409–416.
ICMLICML-2011-Cuturi #performance
Fast Global Alignment Kernels (MC), pp. 929–936.
ICMLICML-2011-DinuzzoOGP #coordination #learning
Learning Output Kernels with Block Coordinate Descent (FD, CSO, PVG, GP), pp. 49–56.
ICMLICML-2011-GermainLLMS #approach
A PAC-Bayes Sample-compression Approach to Kernel Methods (PG, AL, FL, MM, SS), pp. 297–304.
ICMLICML-2011-HuWC #coordination #learning #named #parametricity #scalability #using
BCDNPKL: Scalable Non-Parametric Kernel Learning Using Block Coordinate Descent (EH, BW, SC), pp. 209–216.
ICMLICML-2011-JawanpuriaNR #learning #performance #using
Efficient Rule Ensemble Learning using Hierarchical Kernels (PJ, JSN, GR), pp. 161–168.
ICMLICML-2011-KadriRPDR #functional
Functional Regularized Least Squares Classication with Operator-valued Kernels (HK, AR, PP, ED, AR), pp. 993–1000.
ICMLICML-2011-KimS #on the #robust
On the Robustness of Kernel Density M-Estimators (JK, CDS), pp. 697–704.
ICMLICML-2011-Maaten #learning
Learning Discriminative Fisher Kernels (LvdM), pp. 217–224.
ICMLICML-2011-MachartPARG #learning #probability #rank
Stochastic Low-Rank Kernel Learning for Regression (PM, TP, SA, LR, HG), pp. 969–976.
ICMLICML-2011-OrabonaL #algorithm #learning #multi #optimisation
Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning (FO, JL), pp. 249–256.
ICMLICML-2011-ShinCK
Mapping kernels for trees (KS, MC, TK), pp. 961–968.
ICMLICML-2011-TamuzLBSK #adaptation #learning
Adaptively Learning the Crowd Kernel (OT, CL, SB, OS, AK), pp. 673–680.
ICMLICML-2011-ZhuCX #infinity #process
Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines (JZ, NC, EPX), pp. 617–624.
KDDKDD-2011-ChittaJHJ #approximate #clustering #scalability
Approximate kernel k-means: solution to large scale kernel clustering (RC, RJ, TCH, AKJ), pp. 895–903.
KDDKDD-2011-CotterSK #approach
A GPU-tailored approach for training kernelized SVMs (AC, NS, JK), pp. 805–813.
MLDMMLDM-2011-XuGC #adaptation #learning #multi
Adaptive Kernel Diverse Density Estimate for Multiple Instance Learning (TX, IG, DKYC), pp. 185–198.
PEPMPEPM-2011-CaretteES #generative #geometry
A generative geometric kernel (JC, ME, SS), pp. 53–62.
SACSAC-2011-LeeKY #linux
Experimenting with system and Libc call interception attacks on ARM-based Linux kernel (HcL, CHK, JHY), pp. 631–632.
SACSAC-2011-ShimadaKLCN #composition #design #embedded #functional
Design issues in composition kernels for highly functional embedded systems (HS, YK, THL, AC, TN), pp. 338–345.
ASPLOSASPLOS-2011-HofmannDKRW #operating system
Ensuring operating system kernel integrity with OSck (OSH, AMD, SK, IR, EW), pp. 279–290.
DACDAC-2011-DellingerGR #linux #multi #realtime
ChronOS Linux: a best-effort real-time multiprocessor Linux kernel (MD, PG, BR), pp. 474–479.
DATEDATE-2011-Wang #coordination #gpu #power management
Coordinate strip-mining and kernel fusion to lower power consumption on GPU (GW), pp. 1218–1219.
LCTESLCTES-2011-SahaLM #approach #linux
An approach to improving the structure of error-handling code in the linux kernel (SS, JLL, GM), pp. 41–50.
PDPPDP-2011-SchmidtBGBF #detection #in the cloud
Malware Detection and Kernel Rootkit Prevention in Cloud Computing Environments (MS, LB, PG, DB, BF), pp. 603–610.
SOSPSOSP-2011-ErlingssonPPB #clustering #distributed #named
Fay: extensible distributed tracing from kernels to clusters (ÚE, MP, SP, MB), pp. 311–326.
ICSTICST-2011-RubanovS #linux #runtime #verification
Runtime Verification of Linux Kernel Modules Based on Call Interception (VVR, EAS), pp. 180–189.
ISSTAISSTA-2011-Rubio-GonzalezL #fault #interactive #linux #pointer
Defective error/pointer interactions in the Linux kernel (CRG, BL), pp. 111–121.
ICSMEICSM-2010-CorazzaMMS #approach #clone detection #detection
A Tree Kernel based approach for clone detection (AC, SDM, VM, GS), pp. 1–5.
CIAACIAA-2010-AllauzenCM #automaton #scalability
Large-Scale Training of SVMs with Automata Kernels (CA, CC, MM), pp. 17–27.
ICMLICML-2010-BhadraBBB #matrix #nondeterminism #robust
Robust Formulations for Handling Uncertainty in Kernel Matrices (SB, SB, CB, ABT), pp. 71–78.
ICMLICML-2010-CortesMR #algorithm #learning
Two-Stage Learning Kernel Algorithms (CC, MM, AR), pp. 239–246.
ICMLICML-2010-CortesMR10a #bound #learning
Generalization Bounds for Learning Kernels (CC, MM, AR), pp. 247–254.
ICMLICML-2010-CostaG #distance #performance
Fast Neighborhood Subgraph Pairwise Distance Kernel (FC, KDG), pp. 255–262.
ICMLICML-2010-HueV #learning #on the
On learning with kernels for unordered pairs (MH, JPV), pp. 463–470.
ICMLICML-2010-XuJYKL #learning #multi #performance
Simple and Efficient Multiple Kernel Learning by Group Lasso (ZX, RJ, HY, IK, MRL), pp. 1175–1182.
ICPRICPR-2010-AsheriRPR #adaptation #fault #framework #process
A Gaussian Process Regression Framework for Spatial Error Concealment with Adaptive Kernels (HA, HRR, NP, MHR), pp. 4541–4544.
ICPRICPR-2010-BaghshahS #constraints #learning #performance
Efficient Kernel Learning from Constraints and Unlabeled Data (MSB, SBS), pp. 3364–3367.
ICPRICPR-2010-BicegoMMAF #2d #recognition #using
2D Shape Recognition Using Information Theoretic Kernels (MB, AFTM, VM, PMQA, MATF), pp. 25–28.
ICPRICPR-2010-BouboulisTS #image
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces (PB, ST, KS), pp. 2660–2663.
ICPRICPR-2010-CarliBBM #generative #modelling
Nonlinear Mappings for Generative Kernels on Latent Variable Models (ACC, MB, SB, VM), pp. 2134–2137.
ICPRICPR-2010-DupeBBLE
Kernel-Based Implicit Regularization of Structured Objects (FXD, SB, LB, OL, AE), pp. 2142–2145.
ICPRICPR-2010-GaoHLZW #detection
Local Outlier Detection Based on Kernel Regression (JG, WH, WL, Z(Z, OW), pp. 585–588.
ICPRICPR-2010-GonenA #locality #multi
Localized Multiple Kernel Regression (MG, EA), pp. 1425–1428.
ICPRICPR-2010-GriptonL #semistructured data #using
Kernel Domain Description with Incomplete Data: Using Instance-Specific Margins to Avoid Imputation (AG, WL), pp. 2921–2924.
ICPRICPR-2010-HasanbelliuGP #algorithm #online #recursion
A Recursive Online Kernel PCA Algorithm (EH, LGSG, JCP), pp. 169–172.
ICPRICPR-2010-HassanCG #documentation #image #retrieval #using
Document Image Retrieval Using Feature Combination in Kernel Space (EH, SC, MG), pp. 2009–2012.
ICPRICPR-2010-HaugeardPG #graph #image #retrieval #taxonomy
Kernel on Graphs Based on Dictionary of Paths for Image Retrieval (JEH, SPF, PHG), pp. 2965–2968.
ICPRICPR-2010-JhuoL #learning #multi #recognition
Boosted Multiple Kernel Learning for Scene Category Recognition (IHJ, DTL), pp. 3504–3507.
ICPRICPR-2010-JingLYBY #analysis
Kernel Uncorrelated Adjacent-class Discriminant Analysis (XYJ, SL, YFY, LSB, JY), pp. 706–709.
ICPRICPR-2010-KristanL #estimation #online
Online Discriminative Kernel Density Estimation (MK, AL), pp. 581–584.
ICPRICPR-2010-LariosSSMLD #identification #random
Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification (NL, BS, LGS, GMM, JL, TGD), pp. 2624–2627.
ICPRICPR-2010-LiS #multi
Nonlinear Combination of Multiple Kernels for Support Vector Machines (JL, SS), pp. 2889–2892.
ICPRICPR-2010-MehmoodN #detection #using
Anomaly Detection for Longwave FLIR Imagery Using Kernel Wavelet-RX (AM, NMN), pp. 1385–1388.
ICPRICPR-2010-RicciTZ #learning
Learning Pedestrian Trajectories with Kernels (ER, FT, GZ), pp. 149–152.
ICPRICPR-2010-Sato #classification #design #learning
A New Learning Formulation for Kernel Classifier Design (AS), pp. 2897–2900.
ICPRICPR-2010-TanakaIKM #fault
A Relationship Between Generalization Error and Training Samples in Kernel Regressors (AT, HI, MK, MM), pp. 1421–1424.
ICPRICPR-2010-TumaIP #classification #set #using
Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets (MT, CI, MP), pp. 1011–1014.
ICPRICPR-2010-WangJHT #higher-order #learning #multi
Multiple Kernel Learning with High Order Kernels (SW, SJ, QH, QT), pp. 2138–2141.
ICPRICPR-2010-WangLGL #3d #comparison #difference
3D Model Comparison through Kernel Density Matching (YW, TL, RG, WL), pp. 3159–3162.
ICPRICPR-2010-YaegashiY #learning #multi #recognition #using
Geotagged Photo Recognition Using Corresponding Aerial Photos with Multiple Kernel Learning (KY, KY), pp. 3272–3275.
ICPRICPR-2010-ZhangLD #approach #learning #multi #named #novel
AdaMKL: A Novel Biconvex Multiple Kernel Learning Approach (ZZ, ZNL, MSD), pp. 2126–2129.
ICPRICPR-2010-ZhangWL #categorisation #learning
Learning the Kernel Combination for Object Categorization (DZ, XW, BL), pp. 2929–2932.
ICPRICPR-2010-ZhangZZLL #classification #enterprise
Gaussian ERP Kernel Classifier for Pulse Waveforms Classification (DZ, WZ, DZ, YL, NL), pp. 2736–2739.
ICPRICPR-2010-ZhangZZZ #classification #metric #using
Time Series Classification Using Support Vector Machine with Gaussian Elastic Metric Kernel (DZ, WZ, DZ, HZ), pp. 29–32.
ICPRICPR-2010-ZouY #image #learning
Learning the Relationship Between High and Low Resolution Images in Kernel Space for Face Super Resolution (WWWZ, PCY), pp. 1152–1155.
KDDKDD-2010-DasMSO #algorithm #case study #detection #learning #multi #safety
Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study (SD, BLM, ANS, NCO), pp. 47–56.
KDDKDD-2010-HeLC #scalability #similarity
Scalable similarity search with optimized kernel hashing (JH, WL, SFC), pp. 1129–1138.
KDDKDD-2010-ReichartzKP #dependence #semantics
Semantic relation extraction with kernels over typed dependency trees (FR, HK, GP), pp. 773–782.
KDIRKDIR-2010-GuderSC #modelling #quality
Integrated Instance-based and Kernel Methods for Power Quality Knowledge Modeling (MG, ÖS, ), pp. 352–357.
KDIRKDIR-2010-NcirEB #clustering
Kernel Overlapping K-Means for Clustering in Feature Space (CEBN, NE, PB), pp. 250–255.
KEODKEOD-2010-ArdilaAL #learning #multi #ontology
Multiple Kernel Learning for Ontology Instance Matching (DA, JA, FL), pp. 311–318.
SPLCSPLC-2010-LotufoSBCW #evolution #linux #variability
Evolution of the Linux Kernel Variability Model (RL, SS, TB, KC, AW), pp. 136–150.
FSEFSE-2010-LiG #gpu #scalability #smt #verification
Scalable SMT-based verification of GPU kernel functions (GL, GG), pp. 187–196.
SACSAC-2010-KuuskeriLM #collaboration #peer-to-peer
Peer-to-peer collaboration in the lively kernel (JK, JL, TM), pp. 812–817.
DATEDATE-2010-KhalighR #adaptation #modelling #parallel #simulation
Modeling constructs and kernel for parallel simulation of accuracy adaptive TLMs (RSK, MR), pp. 1183–1188.
OSDIOSDI-2010-EricksonMBO #concurrent #detection #effectiveness
Effective Data-Race Detection for the Kernel (JE, MM, SB, KO), pp. 151–162.
ICDARICDAR-2009-MansjurWJ #automation #categorisation #classification #learning #topic #using
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization (DSM, TSW, BHJ), pp. 1086–1090.
ICDARICDAR-2009-PerronninR
Fisher Kernels for Handwritten Word-spotting (FP, JARS), pp. 106–110.
JCDLJCDL-2009-LiC #approach #graph #machine learning #predict #recommendation
Recommendation as link prediction: a graph kernel-based machine learning approach (XL, HC), pp. 213–216.
SIGMODSIGMOD-2009-ZhangYCPT #estimation
Kernel-based skyline cardinality estimation (ZZ, YY, RC, DP, AKHT), pp. 509–522.
ICSMEICSM-2009-WangWYZY #evolution #linux #network #novel
Linux kernels as complex networks: A novel method to study evolution (LW, ZW, CY, LZ, QY), pp. 41–50.
ICFPICFP-2009-KleinDE #case study #experience #verification
Experience report: seL4: formally verifying a high-performance microkernel (GK, PD, KE), pp. 91–96.
CIKMCIKM-2009-ChenWL #learning #novel #rank
Learning to rank with a novel kernel perceptron method (XwC, HW, XL), pp. 505–512.
CIKMCIKM-2009-FeiH #graph
L2 norm regularized feature kernel regression for graph data (HF, JH), pp. 593–600.
CIKMCIKM-2009-KobayakawaKTOKT #analysis #classification #using
Opinion classification with tree kernel SVM using linguistic modality analysis (TSK, TK, HT, NO, JDK, JT), pp. 1791–1794.
CIKMCIKM-2009-ParkR #analysis #information retrieval #semantics #using
Kernel latent semantic analysis using an information retrieval based kernel (LAFP, KR), pp. 1721–1724.
CIKMCIKM-2009-VienVCYKC #locality #named #using #visualisation
VRIFA: a nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels (NAV, NHV, TC, HY, SK, BHC), pp. 2081–2082.
ICMLICML-2009-AiolliMS
Route kernels for trees (FA, GDSM, AS), pp. 17–24.
ICMLICML-2009-ChenGR #learning
Learning kernels from indefinite similarities (YC, MRG, BR), pp. 145–152.
ICMLICML-2009-Cortes #learning #performance #question
Invited talk: Can learning kernels help performance? (CC), p. 1.
ICMLICML-2009-KowalskiSR #learning #multi
Multiple indefinite kernel learning with mixed norm regularization (MK, MS, LR), pp. 545–552.
ICMLICML-2009-McFeeL #multi #partial order
Partial order embedding with multiple kernels (BM, GRGL), pp. 721–728.
ICMLICML-2009-TaylorP #approximate #learning
Kernelized value function approximation for reinforcement learning (GT, RP), pp. 1017–1024.
ICMLICML-2009-VarmaB #learning #multi #performance
More generality in efficient multiple kernel learning (MV, BRB), pp. 1065–1072.
ICMLICML-2009-ZhuangTH #learning #named #parametricity
SimpleNPKL: simple non-parametric kernel learning (JZ, IWT, SCHH), pp. 1273–1280.
KDDKDD-2009-ZhongFPZRTV #adaptation
Cross domain distribution adaptation via kernel mapping (EZ, WF, JP, KZ, JR, DST, OV), pp. 1027–1036.
MLDMMLDM-2009-GoncalvesQ #classification #semantics #using
Using Graph-Kernels to Represent Semantic Information in Text Classification (TG, PQ), pp. 632–646.
MLDMMLDM-2009-WangZ #classification
Optimal Double-Kernel Combination for Classification (FW, HZ), pp. 107–122.
SACSAC-2009-LombardiP #linux #named #security #virtual machine
KvmSec: a security extension for Linux kernel virtual machines (FL, RDP), pp. 2029–2034.
SACSAC-2009-MikkonenT #case study #experience #framework #mobile #platform #web
Creating a mobile web application platform: the lively kernel experiences (TM, AT), pp. 177–184.
SOSPSOSP-2009-BaumannBDHIPRSS #architecture #manycore #scalability
The multikernel: a new OS architecture for scalable multicore systems (AB, PB, PÉD, TLH, RI, SP, TR, AS, AS), pp. 29–44.
SOSPSOSP-2009-KleinEHACDEEKNSTW #named #verification
seL4: formal verification of an OS kernel (GK, KE, GH, JA, DC, PD, DE, KE, RK, MN, TS, HT, SW), pp. 207–220.
SOSPSOSP-2009-NightingaleHMHH #multi #named
Helios: heterogeneous multiprocessing with satellite kernels (EBN, OH, RM, CH, GCH), pp. 221–234.
MBTMBT-2009-KimHHK #concurrent #debugging #modelling #testing
Model-based Kernel Testing for Concurrency Bugs through Counter Example Replay (MK, SH, CH, TK), pp. 21–36.
ICALPICALP-A-2008-BodlaenderDFH #on the #polynomial #problem
On Problems without Polynomial Kernels (HLB, RGD, MRF, DH), pp. 563–574.
ICGTICGT-2008-EhrigP #analysis #formal method #graph #model transformation
Formal Analysis of Model Transformations Based on Triple Graph Rules with Kernels (HE, UP), pp. 178–193.
CIKMCIKM-2008-Moschitti #categorisation #relational #semantics #syntax
Kernel methods, syntax and semantics for relational text categorization (AM), pp. 253–262.
CIKMCIKM-2008-ZhangM #composition
Classifying networked entities with modularity kernels (DZ, RM), pp. 113–122.
ICMLICML-2008-AllauzenMT #predict #sequence
Sequence kernels for predicting protein essentiality (CA, MM, AT), pp. 9–16.
ICMLICML-2008-AnWSWCD #analysis #image #multi #process
Hierarchical kernel stick-breaking process for multi-task image analysis (QA, CW, IS, EW, LC, DBD), pp. 17–24.
ICMLICML-2008-Bach #graph
Graph kernels between point clouds (FRB), pp. 25–32.
ICMLICML-2008-ChenY
Training SVM with indefinite kernels (JC, JY), pp. 136–143.
ICMLICML-2008-GonenA #learning #locality #multi
Localized multiple kernel learning (MG, EA), pp. 352–359.
ICMLICML-2008-HoiJ #learning
Active kernel learning (SCHH, RJ), pp. 400–407.
ICMLICML-2008-LuLHE #framework
A reproducing kernel Hilbert space framework for pairwise time series distances (ZL, TKL, YH, DE), pp. 624–631.
ICMLICML-2008-MartinsFASX
Nonextensive entropic kernels (AFTM, MATF, PMQA, NAS, EPX), pp. 640–647.
ICMLICML-2008-OrabonaKC #bound
The projectron: a bounded kernel-based Perceptron (FO, JK, BC), pp. 720–727.
ICMLICML-2008-ReisingerSM #learning #online
Online kernel selection for Bayesian reinforcement learning (JR, PS, RM), pp. 816–823.
ICMLICML-2008-Rosset
Bi-level path following for cross validated solution of kernel quantile regression (SR), pp. 840–847.
ICMLICML-2008-SahbiARK #recognition #robust #using
Robust matching and recognition using context-dependent kernels (HS, JYA, JR, RK), pp. 856–863.
ICMLICML-2008-ShinK
A generalization of Haussler’s convolution kernel: mapping kernel (KS, TK), pp. 944–951.
ICMLICML-2008-SongZSGS #estimation
Tailoring density estimation via reproducing kernel moment matching (LS, XZ, AJS, AG, BS), pp. 992–999.
ICMLICML-2008-SriperumbudurLL #classification #metric
Metric embedding for kernel classification rules (BKS, OAL, GRGL), pp. 1008–1015.
ICMLICML-2008-SzafranskiGR #learning
Composite kernel learning (MS, YG, AR), pp. 1040–1047.
ICMLICML-2008-WangYZ #adaptation #learning #multi
Adaptive p-posterior mixture-model kernels for multiple instance learning (HYW, QY, HZ), pp. 1136–1143.
ICPRICPR-2008-BorsN #estimation #modelling #probability
Kernel bandwidth estimation in methods based on probability density function modelling (AGB, NN), pp. 1–4.
ICPRICPR-2008-ChangFLI #clustering #detection #multi
Clustered Microcalcification detection based on a Multiple Kernel Support Vector Machine with Grouped Features (GF-SVM) (TTC, JF, HWL, HHSI), pp. 1–4.
ICPRICPR-2008-ChoiGCC #analysis #independence
Kernel oriented discriminant analysis for speaker-independent phoneme spaces (HC, RGO, SC, YC), pp. 1–4.
ICPRICPR-2008-FuSHLT #image #learning #multi #set
Multiple kernel learning from sets of partially matching image features (SYF, GS, ZGH, ZzL, MT), pp. 1–4.
ICPRICPR-2008-GhoshM #classification #documentation #similarity #using #xml
Combining content and structure similarity for XML document classification using composite SVM kernels (SG, PM), pp. 1–4.
ICPRICPR-2008-GorisseCPP #approximate #image #performance #retrieval #similarity
Fast approximate kernel-based similarity search for image retrieval task (DG, MC, FP, SPF), pp. 1–4.
ICPRICPR-2008-HuangLL #estimation #image
Image deblurring with blur kernel estimation from a reference image patch (PHH, YML, SHL), pp. 1–4.
ICPRICPR-2008-KawabataHS #agile
A rapid anomalous region extraction method by iterative projection onto kernel eigenspace (SK, SH, KS), pp. 1–4.
ICPRICPR-2008-KuksaHP #detection #performance
Fast protein homology and fold detection with sparse spatial sample kernels (PPK, PHH, VP), pp. 1–4.
ICPRICPR-2008-LebrunPG #graph #image #retrieval
Image retrieval with graph kernel on regions (JL, SPF, PHG), pp. 1–4.
ICPRICPR-2008-LiaoL #learning #novel #robust
A novel robust kernel for appearance-based learning (CTL, SHL), pp. 1–4.
ICPRICPR-2008-LiCS #optimisation #predict #video
An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking (ZL, JC, NNS), pp. 1–4.
ICPRICPR-2008-LiuDJM #3d #robust
Kernel functions for robust 3D surface registration with spectral embeddings (XL, AD, MJ, WM), pp. 1–4.
ICPRICPR-2008-LiuWBM #learning #linear
Semi-supervised learning by locally linear embedding in kernel space (RL, YW, TB, DM), pp. 1–4.
ICPRICPR-2008-MaCL #collaboration #constraints #invariant #multi
Multi-cue collaborative kernel tracking with cross ratio invariant constraint (LM, JC, HL), pp. 1–4.
ICPRICPR-2008-MottlLSY #online #verification
Signature verification based on fusion of on-line and off-line kernels (VM, ML, VS, AY), pp. 1–4.
ICPRICPR-2008-SharmaCS #classification
Bag-of-features kernel eigen spaces for classification (GS, SC, JBS), pp. 1–4.
ICPRICPR-2008-YiAC #invariant #using
Orientation and scale invariant mean shift using object mask-based kernel (KMY, HSA, JYC), pp. 1–4.
KDDKDD-2008-ChenJCLWY #classification #learning
Learning subspace kernels for classification (JC, SJ, BC, QL, MW, JY), pp. 106–114.
KDDKDD-2008-WangD #classification #semantics #using #wiki
Building semantic kernels for text classification using wikipedia (PW, CD), pp. 713–721.
KDDKDD-2008-YuJ #using
Training structural svms with kernels using sampled cuts (CNJY, TJ), pp. 794–802.
RecSysRecSys-2008-RendleS #matrix #modelling #recommendation #scalability
Online-updating regularized kernel matrix factorization models for large-scale recommender systems (SR, LST), pp. 251–258.
SIGIRSIGIR-2008-PanTLL #classification #semantics
Question classification with semantic tree kernel (YP, YT, LL, YL), pp. 837–838.
ICSEICSE-2008-Spinellis
A tale of four kernels (DS), pp. 381–390.
SACSAC-2008-LaRosaXM #mining
Frequent pattern mining for kernel trace data (CL, LX, KM), pp. 880–885.
SACSAC-2008-SchobelP #case study #clustering #cpu #research #scheduling #using
Kernel-mode scheduling server for CPU partitioning: a case study using the Windows research kernel (MS, AP), pp. 1700–1704.
DATEDATE-2008-SingheeSR #correlation #performance #statistics
Exploiting Correlation Kernels for Efficient Handling of Intra-Die Spatial Correlation, with Application to Statistical Timing (AS, SS, RAR), pp. 856–861.
HPDCHPDC-2008-YouseffSYDW #algebra #linear #memory management
The impact of paravirtualized memory hierarchy on linear algebra computational kernels and software (LY, KS, HY, JD, RW), pp. 141–152.
OSDIOSDI-2008-GuoWTLXWKZ #named
R2: An Application-Level Kernel for Record and Replay (ZG, XW, JT, XL, ZX, MW, MFK, ZZ), pp. 193–208.
ICDARICDAR-2007-ChenW #documentation #image
Exploiting Fisher Kernels in Decoding Severely Noisy Document Images (JC, YW), pp. 417–421.
ICDARICDAR-2007-YangJ #recognition #using
Handwritten Chinese Character Recognition Using Modified LDA and Kernel FDA (DY, LJ), pp. 914–918.
ICDARICDAR-2007-YangJHH #online #polynomial #recognition
Kernel Modified Quadratic Discriminant Function for Online Handwritten Chinese Characters Recognition (DY, LJ, QH, TH), pp. 38–42.
JCDLJCDL-2007-ShimboIM #analysis #evaluation #metric #recommendation #research
Evaluation of kernel-based link analysis measures on research paper recommendation (MS, TI, YM), pp. 354–355.
MSRMSR-2007-LivieriHMI #analysis #evolution #linux #using
Analysis of the Linux Kernel Evolution Using Code Clone Coverage (SL, YH, MM, KI), p. 22.
ICALPICALP-2007-GuoN #graph #linear #np-hard #problem
Linear Problem Kernels for NP-Hard Problems on Planar Graphs (JG, RN), pp. 375–386.
CIKMCIKM-2007-BloehdornM #semantics
Structure and semantics for expressive text kernels (SB, AM), pp. 861–864.
ECIRECIR-2007-BloehdornM #classification #semantics
Combined Syntactic and Semantic Kernels for Text Classification (SB, AM), pp. 307–318.
ICMLICML-2007-BhattacharyaBC #classification
Structural alignment based kernels for protein structure classification (SB, CB, NRC), pp. 73–80.
ICMLICML-2007-CaoSSYC #feature model
Feature selection in a kernel space (BC, DS, JTS, QY, ZC), pp. 121–128.
ICMLICML-2007-DaiY
Kernel selection forl semi-supervised kernel machines (GD, DYY), pp. 185–192.
ICMLICML-2007-GeurtsWd
Gradient boosting for kernelized output spaces (PG, LW, FdB), pp. 289–296.
ICMLICML-2007-HoiJL #constraints #learning #matrix #parametricity
Learning nonparametric kernel matrices from pairwise constraints (SCHH, RJ, MRL), pp. 361–368.
ICMLICML-2007-KramerB #performance
Kernelizing PLS, degrees of freedom, and efficient model selection (NK, MLB), pp. 441–448.
ICMLICML-2007-KuzminW #matrix #online
Online kernel PCA with entropic matrix updates (DK, MKW), pp. 465–472.
ICMLICML-2007-MoschittiZ #effectiveness #learning #performance #relational
Fast and effective kernels for relational learning from texts (AM, FMZ), pp. 649–656.
ICMLICML-2007-NilssonSJ #reduction #using
Regression on manifolds using kernel dimension reduction (JN, FS, MIJ), pp. 697–704.
ICMLICML-2007-RakotomamonjyBCG #learning #multi #performance
More efficiency in multiple kernel learning (AR, FRB, SC, YG), pp. 775–782.
ICMLICML-2007-SunJSF #algorithm #learning
A kernel-based causal learning algorithm (XS, DJ, BS, KF), pp. 855–862.
ICMLICML-2007-WachmanK #learning #order
Learning from interpretations: a rooted kernel for ordered hypergraphs (GW, RK), pp. 943–950.
ICMLICML-2007-WangYL #algorithm
A kernel path algorithm for support vector machines (GW, DYY, FHL), pp. 951–958.
ICMLICML-2007-YeCJ #learning #parametricity #programming
Discriminant kernel and regularization parameter learning via semidefinite programming (JY, JC, SJ), pp. 1095–1102.
ICMLICML-2007-ZienO #learning #multi
Multiclass multiple kernel learning (AZ, CSO), pp. 1191–1198.
KDDKDD-2007-DingSJL #framework #learning #recommendation #using
A learning framework using Green’s function and kernel regularization with application to recommender system (CHQD, RJ, TL, HDS), pp. 260–269.
KDDKDD-2007-YeJC #analysis #learning #matrix #polynomial #programming
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming (JY, SJ, JC), pp. 854–863.
MLDMMLDM-2007-EkinciA #recognition #representation
Palmprint Recognition by Applying Wavelet Subband Representation and Kernel PCA (ME, MA), pp. 628–642.
MLDMMLDM-2007-EkinciAG #multi #recognition
Gait Recognition by Applying Multiple Projections and Kernel PCA (ME, MA, EG), pp. 727–741.
MLDMMLDM-2007-KyrgyzovKMC #clustering
Kernel MDL to Determine the Number of Clusters (IOK, OOK, HM, MC), pp. 203–217.
MLDMMLDM-2007-LateckiLP #detection
Outlier Detection with Kernel Density Functions (LJL, AL, DP), pp. 61–75.
MLDMMLDM-2007-WuW #graph #parametricity
Choosing the Kernel Parameters for the Directed Acyclic Graph Support Vector Machines (KPW, SDW), pp. 276–285.
SEKESEKE-2007-YuSC #reuse
Common Coupling as a Measure of Reuse Effort in Kernel-Based Software (LY, SRS, KC), pp. 39–44.
ASEASE-2007-CaiWHW #array #automation #testing
Test automation for kernel code and disk arrays with virtual devices (LZC, RSW, WTH, FW), pp. 505–508.
SACSAC-2007-KinebuchiKN
Constructing machine emulator on portable microkernel (YK, HK, TN), pp. 1197–1198.
SACSAC-2007-NguyenT #detection #towards
Towards a tamper-resistant kernel rootkit detector (AQN, YT), pp. 276–283.
GPCEGPCE-2007-LienhardtSS #component #named #programming
Oz/K: a kernel language for component-based open programming (ML, AS, JBS), pp. 43–52.
CGOCGO-2007-BarthouDCDJ #compilation #composition #optimisation #using
Loop Optimization using Hierarchical Compilation and Kernel Decomposition (DB, SD, PC, AD, WJ), pp. 170–184.
CGOCGO-2007-HeTPDA #operating system
Code Compaction of an Operating System Kernel (HH, JT, SP, SKD, GRA), pp. 283–298.
DATEDATE-2007-ArbeloKLLBSM #architecture #configuration management #video
Mapping control-intensive video kernels onto a coarse-grain reconfigurable architecture: the H.264/AVC deblocking filter (CA, AK, SL, JFL, MB, RS, JYM), pp. 177–182.
PDPPDP-2007-Heroux #algorithm #development
Optimal Kernels to Optimal Solutions: Algorithm and Software Issues in Solver Development (MAH).
SOSPSOSP-2007-SeshadriLQP #named
SecVisor: a tiny hypervisor to provide lifetime kernel code integrity for commodity OSes (AS, ML, NQ, AP), pp. 335–350.
HaskellHaskell-2006-DerrinEKCC #approach #development
Running the manual: an approach to high-assurance microkernel development (PD, KE, GK, DC, MMTC), pp. 60–71.
CIKMCIKM-2006-AssfalgBK #3d #classification #named #string
3DString: a feature string kernel for 3D object classification on voxelized data (JA, KMB, HPK), pp. 198–207.
CIKMCIKM-2006-HeinzS #resource management #streaming
Resource-aware kernel density estimators over streaming data (CH, BS), pp. 870–871.
ICMLICML-2006-ArgyriouHMP #algorithm
A DC-programming algorithm for kernel selection (AA, RH, CAM, MP), pp. 41–48.
ICMLICML-2006-GeurtsWd
Kernelizing the output of tree-based methods (PG, LW, FdB), pp. 345–352.
ICMLICML-2006-GreeneC #clustering #documentation #problem
Practical solutions to the problem of diagonal dominance in kernel document clustering (DG, PC), pp. 377–384.
ICMLICML-2006-Haffner #learning #performance
Fast transpose methods for kernel learning on sparse data (PH), pp. 385–392.
ICMLICML-2006-HertzBW #classification #learning
Learning a kernel function for classification with small training samples (TH, ABH, DW), pp. 401–408.
ICMLICML-2006-KimMB #analysis
Optimal kernel selection in Kernel Fisher discriminant analysis (SJK, AM, SPB), pp. 465–472.
ICMLICML-2006-KulisSD #learning #matrix #rank
Learning low-rank kernel matrices (BK, MAS, ISD), pp. 505–512.
ICMLICML-2006-LehmannS #probability
A probabilistic model for text kernels (ADL, JST), pp. 537–544.
ICMLICML-2006-LewisJN
Nonstationary kernel combination (DPL, TJ, WSN), pp. 553–560.
ICMLICML-2006-Memisevic
Kernel information embeddings (RM), pp. 633–640.
ICMLICML-2006-SindhwaniKC
Deterministic annealing for semi-supervised kernel machines (VS, SSK, OC), pp. 841–848.
ICMLICML-2006-TeoV #array #performance #string #using
Fast and space efficient string kernels using suffix arrays (CHT, SVNV), pp. 929–936.
ICMLICML-2006-WingateS #linear #modelling #predict #probability
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems (DW, SPS), pp. 1017–1024.
ICMLICML-2006-ZhangK #matrix #performance
Block-quantized kernel matrix for fast spectral embedding (KZ, JTK), pp. 1097–1104.
ICPRICPR-v1-2006-LiCF #hybrid #set
Hybrid Kernel Machine Ensemble for Imbalanced Data Sets (PL, KLC, WF), pp. 1108–1111.
ICPRICPR-v1-2006-WashizawaY
Non-linear Wiener filter in reproducing kernel Hilbert space (YW, YY), pp. 967–970.
ICPRICPR-v1-2006-ZhangG #human-computer #interface #locality
A Kernel-based Signal Localization Method for NIRS Brain-computer Interfaces (HZ, CG), pp. 1158–1161.
ICPRICPR-v2-2006-AndelicSKK #hybrid #modelling #speech #using
A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models (EA, MS, MK, SEK), pp. 1158–1161.
ICPRICPR-v2-2006-ChenB06a
Function Dot Product Kernels for Support Vector Machine (GC, PB), pp. 614–617.
ICPRICPR-v2-2006-Huang #predict
A New Kernel Based on Weighted Cross-Correlation Coefficient for SVMs and Its Application on Prediction of T-cell Epitopes (JH), pp. 691–694.
ICPRICPR-v2-2006-InoueNK #analysis #feature model #recognition #string #using
Historical Hand-Written String Recognition by Non-linear Discriminant Analysis using Kernel Feature Selection (RI, HN, NK), pp. 1094–1097.
ICPRICPR-v2-2006-KoideY #symmetry
Asymmetric kernel method and its application to Fisher’s discriminant (NK, YY), pp. 820–824.
ICPRICPR-v2-2006-TarelB #detection #parametricity
Object Predetection Based on Kernel Parametric Distribution Fitting (JPT, SB), pp. 808–811.
ICPRICPR-v2-2006-YanT #adaptation #reduction
Dimensionality Reduction with Adaptive Kernels (SY, XT), pp. 626–629.
ICPRICPR-v2-2006-YeSLC #orthogonal
Support vector machine with orthogonal Chebyshev kernel (NY, RS, YL, LC), pp. 752–755.
ICPRICPR-v2-2006-YuanQYZ #approach #classification
An Approach for Constructing Sparse Kernel Classifier (ZY, YQ, YY, NZ), pp. 560–563.
ICPRICPR-v2-2006-ZhengL #analysis #component #learning #locality #problem
Regularized Locality Preserving Learning of Pre-Image Problem in Kernel Principal Component Analysis (WSZ, JHL), pp. 456–459.
ICPRICPR-v2-2006-ZhengLY #learning #problem
Weakly Supervised Learning on Pre-image Problem in Kernel Methods (WSZ, JHL, PCY), pp. 711–715.
ICPRICPR-v3-2006-LeePL #image #re-engineering
Face Reconstruction with Low Resolution Facial Images by Feature Vector Projection in Kernel Space (SWL, JP, SWL), pp. 1179–1182.
ICPRICPR-v3-2006-LiZSCG #analysis #performance #recognition
Bagging Based Efficient Kernel Fisher Discriminant Analysis for Face Recognition (YL, BZ, SS, XC, WG), pp. 523–526.
ICPRICPR-v3-2006-PozdnoukhovB #graph #invariant #pattern matching #pattern recognition #recognition
Graph-based transformation manifolds for invariant pattern recognition with kernel methods (AP, SB), pp. 1228–1231.
ICPRICPR-v3-2006-QiuXT #clustering #feedback #performance #using
Efficient Relevance Feedback Using Semi-supervised Kernel-specified K-means Clustering (BQ, CX, QT), pp. 316–319.
ICPRICPR-v3-2006-SandersonG #markov #on the #sequence
On Authorship Attribution via Markov Chains and Sequence Kernels (CS, SG), pp. 437–440.
ICPRICPR-v3-2006-TangkuampienS #analysis #component
Human Motion De-noising via Greedy Kernel Principal Component Analysis Filtering (TT, DS), pp. 457–460.
ICPRICPR-v3-2006-YamazakiCX #analysis #component #image #independence #using
Separating Reflections from Images Using Kernel Independent Component Analysis (MY, YWC, GX), pp. 194–197.
ICPRICPR-v3-2006-ZhangLG #memory management #recognition
Face Recognition by Combining Kernel Associative Memory and Gabor Transforms (BZ, CL, YG), pp. 465–468.
ICPRICPR-v4-2006-ChaoTWC #framework #problem #testing #verification
A Kernel-based Discrimination Framework for Solving Hypothesis Testing Problems with Application to Speaker Verification (YHC, WHT, HMW, RCC), pp. 229–232.
ICPRICPR-v4-2006-DiegoM
Kernel Procrustes (IMdD, AM), pp. 237–240.
ICPRICPR-v4-2006-KropotovPVV #on the #principle #using
On Kernel Selection in Relevance Vector Machines Using Stability Principle (DK, NP, OV, DV), pp. 233–236.
ICPRICPR-v4-2006-NeuhausB #graph
A Convolution Edit Kernel for Error-tolerant Graph Matching (MN, HB), pp. 220–223.
ICPRICPR-v4-2006-PozdnoukhovB06a #graph #invariant #pattern matching #pattern recognition #recognition
Graph-based transformation manifolds for invariant pattern recognition with kernel methods (AP, SB), p. 956.
ICPRICPR-v4-2006-WangR #analysis #recognition
Kernel Fisher Discriminant Analysis for Palmprint Recognition (YW, QR), pp. 457–460.
ICPRICPR-v4-2006-YuH #graph #string
String Kernels for Matching Seriated Graphs (HY, ERH), pp. 224–228.
KDDKDD-2006-HoiLC #classification #learning
Learning the unified kernel machines for classification (SCHH, MRL, EYC), pp. 187–196.
KDDKDD-2006-TsangKK #feature model #performance #set
Efficient kernel feature extraction for massive data sets (IWT, AK, JTK), pp. 724–729.
AdaEuropeAdaEurope-2006-BreuerP #fault #linux #source code #static analysis
One Million (LOC) and Counting: Static Analysis for Errors and Vulnerabilities in the Linux Kernel Source Code (PTB, SP), pp. 56–70.
SACSAC-2006-ChoiBS #design #implementation #linux #programming #robust
Design and implementation of a kernel resource protector for robustness of Linux module programming (JC, SB, SYS), pp. 1477–1481.
SACSAC-2006-FabryD #aspect-oriented #named #transaction
KALA: Kernel Aspect language for advanced transactions (JF, TD), pp. 1615–1620.
SACSAC-2006-SoaresB #parametricity #using
Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features (CS, PB), pp. 564–568.
SACSAC-2006-YuJV #privacy #using
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data (HY, XJ, JV), pp. 603–610.
GPCEGPCE-2006-YanagisawaKC #aspect-oriented
A dynamic aspect-oriented system for OS kernels (YY, KK, SC), pp. 69–78.
ICSTSAT-2006-KullmannLM #agile #categorisation #normalisation #satisfiability
Categorisation of Clauses in Conjunctive Normal Forms: Minimally Unsatisfiable Sub-clause-sets and the Lean Kernel (OK, IL, JMS), pp. 22–35.
CBSECBSE-2005-DiazGRRST
A CCA-compliant Nuclear Power Plant Simulator Kernel (MD, DG, SR, BR, ES, JMT), pp. 283–297.
SEFMSEFM-2005-GrandySR #java #object-oriented #verification
Object Oriented Verification Kernels for Secure Java Applications (HG, KS, WR), pp. 170–179.
ICEISICEIS-v4-2005-BoppH #architecture #distributed #mobile
A Microkernel Architecture for Distributed Mobile Environments (TB, TH), pp. 151–156.
ICMLICML-2005-BachJ #composition #predict #rank
Predictive low-rank decomposition for kernel methods (FRB, MIJ), pp. 33–40.
ICMLICML-2005-FrohlichWSZ #graph
Optimal assignment kernels for attributed molecular graphs (HF, JKW, FS, AZ), pp. 225–232.
ICMLICML-2005-GirolamiR #learning #modelling
Hierarchic Bayesian models for kernel learning (MG, SR), pp. 241–248.
ICMLICML-2005-KulisBDM #approach #clustering #graph
Semi-supervised graph clustering: a kernel approach (BK, SB, ISD, RJM), pp. 457–464.
ICMLICML-2005-MenchettiCF #composition
Weighted decomposition kernels (SM, FC, PF), pp. 585–592.
ICMLICML-2005-WangS #classification
New kernels for protein structural motif discovery and function classification (CW, SDS), pp. 940–947.
KDDKDD-2005-DhillonGK #algorithm #clustering #graph #multi #performance
A fast kernel-based multilevel algorithm for graph clustering (ISD, YG, BK), pp. 629–634.
KDDKDD-2005-FujimakiYM #approach #detection #problem #using
An approach to spacecraft anomaly detection problem using kernel feature space (RF, TY, KM), pp. 401–410.
KDDKDD-2005-ItoSKM #analysis
Application of kernels to link analysis (TI, MS, TK, YM), pp. 586–592.
KDDKDD-2005-Momma #performance #scalability
Efficient computations via scalable sparse kernel partial least squares and boosted latent features (MM), pp. 654–659.
KDDKDD-2005-WuCP #distance
Formulating distance functions via the kernel trick (GW, EYC, NP), pp. 703–709.
MLDMMLDM-2005-MottlKSM #data mining #mining #multi
Principles of Multi-kernel Data Mining (VM, OK, OS, IBM), pp. 52–61.
SIGIRSIGIR-2005-ZhangCL #classification #multi
Text classification with kernels on the multinomial manifold (DZ, XC, WSL), pp. 266–273.
GPCEGPCE-2005-TanterN #aspect-oriented #multi
A Versatile Kernel for Multi-language AOP (ÉT, JN), pp. 173–188.
DATEDATE-2005-Dubrova #testing
Structural Testing Based on Minimum Kernels (ED), pp. 1168–1173.
DATEDATE-2005-HassanSTI #simulation
RTK-Spec TRON: A Simulation Model of an ITRON Based RTOS Kernel in SystemC (MAH, KS, YT, MI), pp. 554–559.
LCTESLCTES-2005-ChanetSBPB #linux
System-wide compaction and specialization of the linux kernel (DC, BDS, BDB, LVP, KDB), pp. 95–104.
WCREWCRE-2004-EichbergMOS #development #named
XIRC: A Kernel for Cross-Artifact Information Engineering in Software Development Environments (ME, MM, KO, TS), pp. 182–191.
ICALPICALP-2004-FominT #algorithm #exponential #graph #linear #performance
Fast Parameterized Algorithms for Graphs on Surfaces: Linear Kernel and Exponential Speed-Up (FVF, DMT), pp. 581–592.
ICMLICML-2004-BachLJ #algorithm #learning #multi
Multiple kernel learning, conic duality, and the SMO algorithm (FRB, GRGL, MIJ).
ICMLICML-2004-CortesM
Distribution kernels based on moments of counts (CC, MM).
ICMLICML-2004-FungDBR #algorithm #performance #using
A fast iterative algorithm for fisher discriminant using heterogeneous kernels (GF, MD, JB, RBR).
ICMLICML-2004-HamLMS #reduction
A kernel view of the dimensionality reduction of manifolds (JH, DDL, SM, BS).
ICMLICML-2004-Jebara #multi
Multi-task feature and kernel selection for SVMs (TJ).
ICMLICML-2004-KashimaT #algorithm #graph #learning #sequence
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs (HK, YT).
ICMLICML-2004-LaffertyZL #clique #random #representation
Kernel conditional random fields: representation and clique selection (JDL, XZ, YL).
ICMLICML-2004-MaheUAPV #graph
Extensions of marginalized graph kernels (PM, NU, TA, JLP, JPV).
ICMLICML-2004-NguyenWJ #classification #detection #distributed #using
Decentralized detection and classification using kernel methods (XN, MJW, MIJ).
ICMLICML-2004-OngMCS #learning
Learning with non-positive kernels (CSO, XM, SC, AJS).
ICMLICML-2004-WeinbergerSS #learning #matrix #reduction
Learning a kernel matrix for nonlinear dimensionality reduction (KQW, FS, LKS).
ICMLICML-2004-ZhangYK #algorithm #learning #matrix #using
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm (ZZ, DYY, JTK).
ICPRICPR-v1-2004-Ben-ArtziHH
Filtering with Gray-Code Kernels (GBA, HHO, YHO), pp. 556–559.
ICPRICPR-v1-2004-Chen #robust
M-Estimator based Robust Kernels for Support Vector Machines (JHC), pp. 168–171.
ICPRICPR-v1-2004-ChengLLC #classification #component #independence #using
Texture Classification Using Kernel Independent Component Analysi (JC, QL, HL, YWC), pp. 620–623.
ICPRICPR-v1-2004-Horikawa #classification #comparison #invariant
Comparison of Support Vector Machines with Autocorrelation Kernels for Invariant Texture Classification (YH), pp. 660–663.
ICPRICPR-v1-2004-ShenB #analysis #recognition
Gabor Wavelets and Kernel Direct Discriminant Analysis for Face Recognition (LS, LB), pp. 284–287.
ICPRICPR-v2-2004-CaputoWN #categorisation
Object Categorization via Local Kernels (BC, CW, MEN), pp. 132–135.
ICPRICPR-v2-2004-CawleyT #performance
Efficient Model Selection for Kernel Logistic Regression (GCC, NLCT), pp. 439–442.
ICPRICPR-v2-2004-DaiQJ #analysis #pattern matching #pattern recognition #recognition
A Kernel Fractional-Step Nonlinear Discriminant Analysis for Pattern Recognition (GD, YQ, SJ), pp. 431–434.
ICPRICPR-v2-2004-HalawaniB #evaluation #image #retrieval
Image Retrieval by Local Evaluation of Nonlinear Kernel Functions around Salient Points (AH, HB), pp. 955–960.
ICPRICPR-v2-2004-LiuTLM #analysis #recognition
Kernel Scatter-Difference Based Discriminant Analysis For Face Recognition (QL, XT, HL, SM), pp. 419–422.
ICPRICPR-v2-2004-Nagao #approach #feature model
Bayesian Approach with Nonlinear Kernels to Feature Extraction (KN), pp. 153–156.
ICPRICPR-v2-2004-NeedhamB #multi
Multi-Resolution Template Kernels (CJN, RDB), pp. 233–236.
ICPRICPR-v2-2004-SaadiTC #analysis
Optimally Regularised Kernel Fisher Discriminant Analysis (KS, NLCT, GCC), pp. 427–430.
ICPRICPR-v2-2004-WashizawaY #classification #pattern matching #pattern recognition #recognition
Kernel Sample Space Projection Classifier for Pattern Recognition (YW, YY), pp. 435–438.
ICPRICPR-v2-2004-ZhangHHL
Kernel-Based Method for Tracking Objects with Rotation and Translation (HZ, ZH, WH, LL), pp. 728–731.
ICPRICPR-v2-2004-ZhangHHZ #classification #visual notation
Kernel Autoassociator with Applications to Visual Classification (HZ, WH, ZH, BZ), pp. 443–446.
ICPRICPR-v3-2004-BenoitF
Steerable Kernels for Arbitrarily-Sampled Spaces (SB, FPF), pp. 578–581.
ICPRICPR-v3-2004-GurwiczL #agile #estimation #network
Rapid Spline-based Kernel Density Estimation for Bayesian Networks (YG, BL), pp. 700–703.
ICPRICPR-v3-2004-Hotta #recognition #robust
Support Vector Machine with Local Summation Kernel for Robust Face Recognition (KH), pp. 482–485.
ICPRICPR-v3-2004-JagmohanSA #estimation #using
Dense Stereo Matching Using Kernel Maximum Likelihood Estimation (AJ, MKS, NA), pp. 28–31.
ICPRICPR-v3-2004-LiuCLM #distance #image #re-engineering
Distance Based Kernel PCA Image Reconstruction (QL, JC, HL, SM), pp. 670–673.
ICPRICPR-v3-2004-PozdnoukhovB #classification #image #invariant
Tangent Vector Kernels for Invariant Image Classification with SVMs (AP, SB), pp. 486–489.
ICPRICPR-v4-2004-QinandS #algorithm #analysis #clustering
Kernel Neural Gas Algorithms with Application to Cluster Analysis (AKQ, PNS), pp. 617–620.
ICPRICPR-v4-2004-QinandS04a #algorithm #learning #novel #prototype
A Novel Kernel Prototype-Based Learning Algorithm (AKQ, PNS), pp. 621–624.
ICPRICPR-v4-2004-TanCZ #image #metric #robust #using
Robust Image Denoising Using Kernel-Induced Measures (KT, SC, DZ), pp. 685–688.
KDDKDD-2004-BiZB
Column-generation boosting methods for mixture of kernels (JB, TZ, KPB), pp. 521–526.
KDDKDD-2004-DhillonGK #clustering #normalisation
Kernel k-means: spectral clustering and normalized cuts (ISD, YG, BK), pp. 551–556.
KDDKDD-2004-HorvathGW #graph #mining #predict
Cyclic pattern kernels for predictive graph mining (TH, TG, SW), pp. 158–167.
SEKESEKE-2004-FengyanZX #algorithm #modelling #parametricity #reliability
A Nonparametric Software Reliability Model Based on Kernel Estimator and Optimum Algorithm (HF, QZ, WX), pp. 13–18.
AdaEuropeAdaEurope-2004-BreuerG #concurrent #detection #linux
Static Deadlock Detection in the Linux Kernel (PTB, MGV), pp. 52–64.
SACSAC-2004-MortonL #design #hardware
A hardware/software kernel for system on chip designs (AM, WML), pp. 869–875.
PDPPDP-2004-Kumova #concept #design #distributed #simulation
Software Design Concepts of a Distributed Simulation Kernel (BIK), pp. 34–39.
ICLPICLP-2004-RayBR #set
Generalised Kernel Sets for Inverse Entailment (OR, KB, AR), pp. 165–179.
VMCAIVMCAI-2004-PaceS #difference #model checking #using
Model Checking Polygonal Differential Inclusions Using Invariance Kernels (GJP, GS), pp. 110–121.
ICMLICML-2003-CumbyR #learning #on the #relational
On Kernel Methods for Relational Learning (CMC, DR), pp. 107–114.
ICMLICML-2003-DeCosteM #approximate #classification #incremental #performance
Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors (DD, DM), pp. 115–122.
ICMLICML-2003-KashimaTI #graph
Marginalized Kernels Between Labeled Graphs (HK, KT, AI), pp. 321–328.
ICMLICML-2003-KlautauJO #classification #comparison #modelling
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers (AK, NJ, AO), pp. 353–360.
ICMLICML-2003-KondorJ #set
A Kernel Between Sets of Vectors (RK, TJ), pp. 361–368.
ICMLICML-2003-KwokT #learning
Learning with Idealized Kernels (JTK, IWT), pp. 400–407.
ICMLICML-2003-KwokT03a #problem
The Pre-Image Problem in Kernel Methods (JTK, IWT), pp. 408–415.
ICMLICML-2003-OngS #machine learning
Machine Learning with Hyperkernels (CSO, AJS), pp. 568–575.
ICMLICML-2003-RosipalTM #classification #linear
Kernel PLS-SVC for Linear and Nonlinear Classification (RR, LJT, BM), pp. 640–647.
ICMLICML-2003-Zhang #learning #metric #multi #representation #scalability #towards
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation (ZZ), pp. 872–879.
ASEASE-2003-AbergLSMM #aspect-oriented #automation #evolution #logic #on the #using
On the automatic evolution of an OS kernel using temporal logic and AOP (RAÅ, JLL, MS, GM, AFLM), pp. 196–204.
SACSAC-2003-Cerrito #estimation #using #visualisation
Data Visualization Using Kernel Density Estimation to Examine Patterns of Physician Practice (PBC), pp. 275–279.
SOSPSOSP-2003-Arpaci-DusseauABDEGNP #policy
Transforming policies into mechanisms with infokernel (ACAD, RHAD, NCB, TED, TJE, HSG, JAN, FIP), pp. 90–105.
SCAMSCAM-J-2001-AntoniolVMP02 #evolution #linux
Analyzing cloning evolution in the Linux kernel (GA, UV, EM, MDP), pp. 755–765.
ICMLICML-2002-DeCoste #classification #distance #geometry #performance
Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry (DD), pp. 99–106.
ICMLICML-2002-GartnerFKS #multi
Multi-Instance Kernels (TG, PAF, AK, AJS), pp. 179–186.
ICMLICML-2002-KashimaK
Kernels for Semi-Structured Data (HK, TK), pp. 291–298.
ICMLICML-2002-KeerthiDSP #algorithm #performance
A Fast Dual Algorithm for Kernel Logistic Regression (SSK, KD, SKS, ANP), pp. 299–306.
ICMLICML-2002-KondorL #graph
Diffusion Kernels on Graphs and Other Discrete Input Spaces (RK, JDL), pp. 315–322.
ICMLICML-2002-LanckrietCBGJ #learning #matrix #programming
Learning the Kernel Matrix with Semi-Definite Programming (GRGL, NC, PLB, LEG, MIJ), pp. 323–330.
ICMLICML-2002-SaundersTS #string
Syllables and other String Kernel Extensions (CS, HT, JST), pp. 530–537.
ICPRICPR-v2-2002-HaasdonkK #distance
Tangent Distance Kernels for Support Vector Machines (BH, DK), pp. 864–868.
ICPRICPR-v2-2002-JainM #classification
Hierarchical Kernel Fitting for Fingerprint Classification and Alignment (AKJ, SM), pp. 469–473.
ICPRICPR-v2-2002-LiuHLM #analysis #recognition
Kernel-Based Optimized Feature Vectors Selection and Discriminant Analysis for Face Recognition (QL, RH, HL, SM), pp. 362–365.
ICPRICPR-v3-2002-AyatCS #named #pattern matching #pattern recognition #recognition
KMOD — A Tw o-Parameter SVM Kernel for Pattern Recognition (NEA, MC, CYS), pp. 331–334.
ICPRICPR-v3-2002-PengHD #adaptation #classification #metric #nearest neighbour
Adaptive Kernel Metric Nearest Neighbor Classification (JP, DRH, HKD), pp. 33–36.
ICPRICPR-v4-2002-CaputoN #classification
To Each According to its Need: Kernel Class Specific Classifiers (BC, HN), pp. 94–97.
ICPRICPR-v4-2002-MottlKK #classification #identification
Support Object Classifiers with Rigid and Elastic Kernel Functions for Face Identification (VM, AK, JK), pp. 205–208.
ICPRICPR-v4-2002-ZhangR #clustering #scalability
A Large Scale Clustering Scheme for Kernel K-Means (RZ, AIR), pp. 289–292.
KDDKDD-2002-BennettME #algorithm #modelling #named
MARK: a boosting algorithm for heterogeneous kernel models (KPB, MM, MJE), pp. 24–31.
AdaEuropeAdaEurope-2002-BinderL #embedded #execution #java #reliability #using
Using a Secure Java Micro-kernel on Embedded Devices for the Reliable Execution of Dynamically Uploaded Applications (WB, BL), pp. 125–135.
DATEDATE-2002-BjorklundL #towards
Towards a Kernel Language for Heterogeneous Computing (DB, JL), p. 1136.
HPDCHPDC-2002-TaylorWGS #parallel #performance #predict #using
Using Kernel Couplings to Predict Parallel Application Performance (VET, XW, JG, RLS), pp. 125–134.
OSDIOSDI-2002-WhitakerSG #performance
Scale and Performance in the Denali Isolation Kernel (AW, MS, SDG), pp. 195–209.
ICDARICDAR-2001-AyatCRS #image #named #pattern matching #pattern recognition #recognition
KMOD — A New Support Vector Machine Kernel with Moderate Decreasing for Pattern Recognition. Application to Digit Image Recognition (NEA, MC, LR, CYS), p. 1215–?.
ICDARICDAR-2001-ZhaoL #documentation #recognition
High-Precision Two-Kernel Chinese Character Recognition in General Document Processing Systems (SLZ, HJL), pp. 617–621.
SCAMSCAM-2001-AntoniolVDCM #clone detection #identification #linux
Identifying Clones in the Linux Kernel (GA, UV, MDP, GC, EM), pp. 92–99.
ICMLICML-2001-CristianiniSL #semantics
Latent Semantic Kernels (NC, JST, HL), pp. 66–73.
ICMLICML-2001-JoachimsCS #categorisation #hypermedia
Composite Kernels for Hypertext Categorisation (TJ, NC, JST), pp. 250–257.
ICMLICML-2001-LawrenceS
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise (NDL, BS), pp. 306–313.
AdaEuropeAdaEurope-2001-Rivas #ada #embedded #realtime
Michael González Harbour: MaRTE OS: An Ada Kernel for Real-Time Embedded Applications (MAR), pp. 305–316.
AdaEuropeAdaEurope-2001-ZamoranoRP #ada #implementation #realtime
Implementing Ada.Real_Time.Clock and Absolute Delays in Real-Time Kernels (JZ, JFR, JAdlP), pp. 317–327.
SACSAC-2001-LauvsetJM #distributed #named
TOS: kernel support for distributed systems management (KJL, DJ, KM), pp. 412–419.
PDPPDP-2001-ArtiagaG #migration #parallel #thread
Running Multithreaded Applications in Exokernel-based Systems: Porting CThreads to Xok (EA, MG), pp. 77–83.
VLDBVLDB-2000-RamsakMFZEB #database
Integrating the UB-Tree into a Database System Kernel (FR, VM, RF, MZ, KE, RB), pp. 263–272.
ITiCSEITiCSE-2000-Holliday #operating system
A kernel-based synchronization assignment for the operating systems course (MAH), p. 184.
ICMLICML-2000-EvgeniouPPP #bound #performance
Bounds on the Generalization Performance of Kernel Machine Ensembles (TE, LPB, MP, TP), pp. 271–278.
ICMLICML-2000-TeowL #parametricity
Selection of Support Vector Kernel Parameters for Improved Generalization (LNT, KFL), pp. 967–974.
ICMLICML-2000-WilliamsS #classification
The Effect of the Input Density Distribution on Kernel-based Classifiers (CKIW, MWS), pp. 1159–1166.
TOOLSTOOLS-EUROPE-2000-DuvalP #design pattern #interactive #object-oriented #using
Using the PAC-Amodeus Model and Design Patterns to Make Interactive an Existing Object-Oriented Kernel (TD, FP), pp. 407–418.
AdaEuropeAdaEurope-2000-PuenteRZ #realtime
An Open Ravenscar Real-Time Kernel for GNAT (JAdlP, JFR, JZ), pp. 5–15.
GPCESAIG-2000-VuducD #automation #case study #code generation #experience
Code Generators for Automatic Tuning of Numerical Kernels: Experiences with FFTW (RV, JD), pp. 190–211.
ASEASE-2000-MartinWTG
Formal Construction of the Mathematically Analyzed Separation Kernel (WM, PW, FST, AG), pp. 133–142.
ICSEICSE-2000-PenixVELW #clustering #verification
Verification of time partitioning in the DEOS scheduler kernel (JP, WV, EE, AL, NW), pp. 488–497.
ICDARICDAR-1999-RemakiC #documentation #image #product line #using #visual notation
Visual Data Extraction from Bi-level Document Images using a Generalized Kernel Family with Compact Support, in Scale-Space (LR, MC), pp. 609–612.
KDDKDD-1999-ZhangRL #database #estimation #performance #scalability #using
Fast Density Estimation Using CF-Kernel for Very Large Databases (TZ, RR, ML), pp. 312–316.
AdaEuropeAdaEurope-1999-ShenCB #ada #implementation #linux #multi
A “Bare-Machine” Implementation of Ada Multi-tasking Beneath the Linux Kernel (HS, AC, TPB), pp. 287–297.
DACDAC-1999-BeniniMMOP #algorithm #approximate #component #optimisation
Kernel-Based Power Optimization of RTL Components: Exact and Approximate Extraction Algorithms (LB, GDM, EM, GO, MP), pp. 247–252.
DATEDATE-1999-MaestreKBSHF #configuration management #scheduling
Kernel Scheduling in Reconfigurable Computing (RM, FJK, NB, HS, RH, MF), pp. 90–96.
OSDIOSDI-1999-FordHLMT #execution #interface #modelling
Interface and Execution Models in the Fluke Kernel (BF, MH, JL, RM, PT), pp. 101–115.
OSDIOSDI-1999-TamchesM #fine-grained #operating system
Fine-Grained Dynamic Instrumentation of Commodity Operating System Kernels (AT, BPM), pp. 117–130.
PDPPDP-1999-GetovWCG #optimisation #performance
Performance optimisations of the NPB FT kernel by special-purpose unroller (VG, YW, LC, KSG), pp. 84–88.
SOSPSOSP-1999-ZuberiPS #named #realtime
EMERALDS: a small-memory real-time microkernel (KMZ, PP, KGS), pp. 277–299.
LICSLICS-1999-ColazzoG #recursion #type system
Subtyping Recursive Types in Kernel Fun (DC, GG), pp. 137–146.
VLDBVLDB-1998-ArunJ #architecture #independence #interface #named
KODA — The Architecture And Interface of a Data Model Independent Kernel (GA, AJ), pp. 671–674.
ITiCSEITiCSE-1998-MayoK #programming
A secure networked laboratory for kernel programming (JM, PK), pp. 175–177.
ICMLICML-1998-FriessCC #algorithm #learning #performance
The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines (TTF, NC, CC), pp. 188–196.
AdaSIGAda-1998-WongL #ada #design #hardware
Kernel Ada to Unify Hardware and Software Design (SW, GL), pp. 28–38.
SACSAC-1998-RussellH #communication #performance #reliability
Efficient kernel support for reliable communication (RDR, PJH), pp. 541–550.
DACDAC-1998-BeniniMLMOP #optimisation
Computational Kernels and their Application to Sequential Power Optimization (LB, GDM, AL, EM, GO, MP), pp. 764–769.
HPDCHPDC-1998-CzechHG #composition #flexibility #protocol
Flexible Protocol Stacks by In-Kernel Composition (CBC, BH, MG), pp. 344–345.
HPCAHPCA-1997-MarkatosK #operating system
User-Level DMA without Operating System Kernel Modification (EPM, MK), pp. 322–331.
SOSPSOSP-1997-FordBBLLS #research
The Flux OSKit: A Substrate for Kernel and Language Research (BF, GB, GB, JL, AL, OS), pp. 38–51.
SOSPSOSP-1997-HartigHLSW #performance
The Performance of µKernel-Based Systems (HH, MH, JL, SS, JW), pp. 66–77.
SOSPSOSP-1997-KaashoekEGBHMPGM #flexibility #performance
Application Performance and Flexibility on Exokernel Systems (MFK, DRE, GRG, HMB, RH, DM, TP, RG, JJ, KM), pp. 52–65.
CADECADE-1997-NieuwenhuisRV #algorithm #automation #data type #deduction #named #similarity
Dedan: A Kernel of Data Structures and Algorithms for Automated Deduction with Equality Clauses (RN, JMR, MÁV), pp. 49–52.
ICFPICFP-1996-Ghelli #complexity #type checking #type system
Complexity of Kernel Fun Subtype Checking (GG), pp. 134–145.
ICPRICPR-1996-DePieroT #adaptation #image #realtime #segmentation #using
Real-time range image segmentation using adaptive kernels and Kalman filtering (FWD, MMT), pp. 573–577.
DACDAC-1996-VercauterenLM96a #architecture #embedded #realtime
A Strategy for Real-Time Kernel Support in Application-Specific HW/SW Embedded Architectures (SV, BL, HDM), pp. 678–683.
PDPPDP-1996-MoureFHL #communication #named
TransCom: A Communication Microkernel for Transputers (JCM, DF, EH, EL), pp. 147–153.
ISSTAISSTA-1996-BarjaktarovicCJ #functional #protocol #specification #using #verification
Formal Specification and Verification of the Kernel Functional Unit of the OSI Session Layer Protocol and Service Using CCS (MB, SKC, KJ), pp. 270–279.
ICMLICML-1995-SmythGF #classification #estimation #using
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (PS, AGG, UMF), pp. 506–514.
SOSPSOSP-1995-EnglerKO #architecture #named #operating system #resource management
Exokernel: An Operating System Architecture for Application-Level Resource Management (DRE, MFK, JO), pp. 251–266.
SOSPSOSP-1995-Liedtke #on the
On micro-Kernel Construction (JL), pp. 237–250.
CAiSECAiSE-1994-Lonchamp #collaboration
A Collaborative Process-Centered Environment Kernel (JL), pp. 28–41.
PDPPDP-1994-LiveseyA #configuration management
A Dynamically Configurable Co-processor For Microkernels (ML, CA), pp. 372–376.
ICDARICDAR-1993-LinSOS #information management #object-oriented
An object-oriented kernel for geographical information systems (YML, TS, YO, MS), pp. 878–881.
SEKESEKE-1993-Weis #design #distributed #object-oriented
Object-Oriented Design of a Distributed Blackboard Kernel (MW), pp. 285–287.
SOSPSOSP-1993-Liedtke #design
Improving IPC by Kernel Design (JL), pp. 175–188.
ICLPICLP-1993-TickB #compilation #evaluation #performance #runtime
Performance Evaluation of Monaco Compiler and Runtime Kernel (ET, CB), pp. 757–773.
SOSPSOSP-WIP-1991-Druschel92 #architecture #composition #orthogonal #why
Modularity and Protection are Orthogonal, or “Why µ-kernel Architectures are Flawed” (PD), p. 22.
SOSPSOSP-WIP-1991-Finlayson92 #communication
Structuring and Communication in the Vanguard OS Kernel (RSF), p. 30.
SOSPSOSP-WIP-1991-MassalinP92 #multi
A Lock-Free Multiprocessor OS Kernel (HM, CP), p. 8.
OOPSLAOOPSLA-1991-YaseenSL
An Extensible Kernel Object Management System (RY, SYWS, HL), pp. 247–263.
SOSPSOSP-1991-AndersonBLL #effectiveness #parallel
Scheduler Activations: Effective Kernel Support for the User-Level Management of Parallelism (TEA, BNB, EDL, HML), pp. 95–109.
CAVCAV-1991-BevierS #proving #specification
Mechanically Checked Proofs of Kernel Specification (WRB, JFSA), pp. 70–82.
ICLPISLP-1991-JansonH #paradigm #programming
Programming Paradigms of the Andorra Kernel Language (SJ, SH), pp. 167–183.
OOPSLAOOPSLA-ECOOP-1990-HabertA #named #object-oriented
COOL: Kernel Support for Object-Oriented Environments (SH, VA), pp. 269–277.
DACDAC-1990-FeghhiMK #design #object-oriented #process
An Object-Oriented Kernel for an Integrated Design and Process Planning System (SJF, MMM, RLK), pp. 437–443.
PPoPPPPoPP-1990-RamkumarK #compilation #implementation #parallel #prolog
A Chare Kernel Implementation of a Parallel Prolog Compiler (BR, LVK), pp. 99–108.
ICLPCLP-1990-HaridiJ90 #prolog
Kernel Andorra Prolog and its Computation Model (SH, SJ), pp. 31–46.
SOSPSOSP-1989-AbrossimovR #memory management #operating system
Generic Virtual Memory Management for Operating System Kernels (VA, MR, MS), pp. 123–136.
SOSPSOSP-1989-HutchinsonPAO #design
RPC in the x-Kernel: Evaluating New Design Techniques (NCH, LLP, MBA, SWO), pp. 91–101.
SOSPSOSP-1989-MassalinP #synthesis #thread
Threads and Input/Output in the Synthesis Kernel (HM, CP), pp. 191–201.
FMVDME-1988-Goldsack #operating system #specification
Specification of an Operating System Kernel FOREST and VDM compared (SJG), pp. 88–100.
LISPLFP-1988-BobrowK #lisp #object-oriented
The Common Lisp Object System Metaobject Kernel: A Status Report (DGB, GK), pp. 309–315.
ECOOPECOOP-1988-DoiKH #concurrent #implementation #object-oriented #operating system #using
An Implementation of an Operating System Kernel Using Concurrent Object-Oriented Language ABCL/c+ (ND, YK, KH), pp. 250–266.
OOPSLAOOPSLA-1988-LaLondeG #backtracking #smalltalk
Building a Backtracking Facility in Smalltalk Without Kernel Support (WRL, MVG), pp. 105–122.
DACDAC-1988-WolfKA #algorithm #logic #multi
A Kernel-Finding State Assignment Algorithm for Multi-Level Logic (WW, KK, JA), pp. 433–438.
SIGMODSIGMOD-1987-PaulSSWD #architecture #database #implementation
Architecture and Implementation of the Darmstadt Database Kernel System (HBP, HJS, MHS, GW, UD), pp. 196–207.
VLDBVLDB-1987-SchollPS #relational
Supporting Flat Relations by a Nested Relational Kernel (MHS, HBP, HJS), pp. 137–146.
OOPSLAOOPSLA-1986-JonesR #distributed #object-oriented
Mach and Matchmaker: Kernel and Language Support for Object-Oriented Distributed Systems (MBJ, RFR), pp. 67–77.
SOSPSOSP-1985-CarrieroG
The S/Net’s Linda Kernel (NC, DG), p. 160.
SIGMODSIGMOD-1984-DielKLSS #data transformation #operating system
Data Management Facilities of an Operating System Kernel (HD, GK, NGL, MS, BS), pp. 58–69.
SOSPSOSP-1983-CheritonZ #distributed #performance
The Distributed V Kernel and its Performance for Diskless Workstations (DRC, WZ), pp. 129–140.
SOSPSOSP-1983-Silverman #operating system #security #verification
Reflections on the Verification of the Security of an Operating System Kernel (JMS), pp. 143–154.
ICSEICSE-1982-BerettaBFNSS #interactive #named
XS-1: An Integrated Interactive System and Its Kernel (GB, HB, PF, JN, JS, HS), pp. 340–349.
CADECADE-1982-LuskMO #architecture #logic
Logic Machine Architecture: Kernel Funtions (ELL, WM, RAO), pp. 70–84.
SOSPSOSP-1981-Bartlett
A NonStop Kernel (JFB), pp. 22–19.
SOSPSOSP-1981-RashidR #communication #named #network #operating system
Accent: A Communication Oriented Network Operating System Kernel (RFR, GGR), pp. 64–75.
SOSPSOSP-J-1979-WalkerKP80 #security #specification #verification
Specification and Verification of the UCLA Unix Security Kernel (BJW, RAK, GJP), pp. 118–131.
SOSPSOSP-1979-WalkerKP #security #specification #verification
Specification and Verification of the UCLA Unix Security Kernel (BJW, RAK, GJP), pp. 64–65.
VLDBVLDB-1977-DownsP #database #design
A Kernel Design for a Secure Data Base Management System (DD, GJP), pp. 507–514.
SOSPSOSP-1977-McDaniel #distributed #metric #named
METRIC: A Kernel Instrumentation System for Distributed Environments (GM), pp. 93–99.
SOSPSOSP-1977-SchroederCS #design #multi
The Multics Kernel Design Project (MDS, DDC, JHS), pp. 43–56.
SOSPSOSP-J-1975-Millen76 #security #validation
Security Kernel Validation in Practice (JKM), pp. 243–250.
SOSPSOSP-1975-Schroeder #multi #security
Engineering a Security Kernel for Multics (MDS), pp. 25–32.
SOSPSOSP-1973-SpierHC #architecture #implementation
An Experimental Implementation on the Kernel/Domain Architecture (MJS, TNH, DNC), pp. 8–21.

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