BibSLEIGH — kernel tag

kernel

kernel

Tag #kernel

818 papers:

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