## Stem loss$ (all stems)

### 90 papers:

- CASE-2015-TomolaMBC #robust
- Robust codiagnosability of discrete-event systems against permanent loss of observations (JHAT, MVM, JCB, LKC), pp. 813–818.
- ICML-2015-BachHBG #learning #performance
- Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs (SHB, BH, JLBG, LG), pp. 381–390.
- ICML-2015-GasseAE #classification #composition #multi #on the #set
- On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property (MG, AA, HE), pp. 2531–2539.
- ICML-2015-YuB #learning
- Learning Submodular Losses with the Lovasz Hinge (JY, MBB), pp. 1623–1631.
- ICML-2015-ZhangL15a #distributed #empirical #named #optimisation #self
- DiSCO: Distributed Optimization for Self-Concordant Empirical Loss (YZ, XL), pp. 362–370.
- ICML-2015-ZhaoZ #optimisation #probability
- Stochastic Optimization with Importance Sampling for Regularized Loss Minimization (PZ, TZ), pp. 1–9.
- HCI-AS-2014-FerreiraB #analysis #elicitation #people #requirements #semantics
- Eliciting Accessibility Requirements for People with Hearing Loss: A Semantic and Norm Analysis (MAMF, RB), pp. 277–288.
- ICML-c1-2014-Shalev-Shwartz0 #coordination #probability
- Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization (SSS, TZ), pp. 64–72.
- ICML-c1-2014-YangSX #classification
- The Coherent Loss Function for Classification (WY, MS, HX), pp. 37–45.
- ICML-c2-2014-BeijbomSKV #multi
- Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting (OB, MJS, DJK, NV), pp. 586–594.
- ICML-c2-2014-HonorioJ #consistency #framework
- A Unified Framework for Consistency of Regularized Loss Minimizers (JH, TSJ), pp. 136–144.
- SEKE-2014-El-KharboutlyGF #analysis #security
- Industry-wise Analysis of Security Breaches in Data Loss Incidents (REK, SSG, LF), pp. 615–619.
- STOC-2013-AzarCG
- The loss of serving in the dark (YA, IRC, IG), pp. 951–960.
- LATA-2013-BenzaidDE #algorithm #complexity
- Duplication-Loss Genome Alignment: Complexity and Algorithm (BB, RD, NEM), pp. 116–127.
- HCI-UC-2013-AhnK #design #interface
- Interface Design for Minimizing Loss of Context in In-situ Remote Robot Control (JgA, GJK), pp. 87–96.
- ICML-c1-2013-KumarLVV #bound
- Near-Optimal Bounds for Cross-Validation via Loss Stability (RK, DL, SV, AV), pp. 27–35.
- ICML-c3-2013-DembczynskiJKWH #approach #classification #multi #optimisation #plugin
- Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization (KD, AJ, WK, WW, EH), pp. 1130–1138.
- ICML-c3-2013-KarS0K #algorithm #learning #on the #online
- On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions (PK, BKS, PJ, HK), pp. 441–449.
- ICML-c3-2013-MineiroK
- Loss-Proportional Subsampling for Subsequent ERM (PM, NK), pp. 522–530.
- ICML-c3-2013-NguyenS #algorithm #classification #optimisation
- Algorithms for Direct 0-1 Loss Optimization in Binary Classification (TN, SS), pp. 1085–1093.
- ICML-c3-2013-NiuJDHS #approach #learning #novel
- Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning (GN, WJ, BD, HH, MS), pp. 10–18.
- RecSys-2013-WestonYW #learning #rank #recommendation #statistics
- Learning to rank recommendations with the k-order statistic loss (JW, HY, RJW), pp. 245–248.
- ICML-2012-BalleQC #learning #modelling #optimisation
- Local Loss Optimization in Operator Models: A New Insight into Spectral Learning (BB, AQ, XC), p. 236.
- ICML-2012-Ben-DavidLSS #classification #fault #using
- Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss (SBD, DL, NS, KS), p. 16.
- ICML-2012-DembczynskiKH #consistency #multi #ranking
- Consistent Multilabel Ranking through Univariate Losses (KD, WK, EH), p. 175.
- ICML-2012-KumarPK #learning #modelling #nondeterminism
- Modeling Latent Variable Uncertainty for Loss-based Learning (MPK, BP, DK), p. 29.
- ICML-2012-MenonJVEO #predict #ranking
- Predicting accurate probabilities with a ranking loss (AKM, XJ, SV, CE, LOM), p. 88.
- ICML-2012-NeufeldYZKS #reduction
- Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations (JN, YY, XZ, RK, DS), p. 191.
- ICML-2012-ReidWS #design #multi
- The Convexity and Design of Composite Multiclass Losses (MDR, RCW, PS), p. 36.
- ICPR-2012-RenO #authentication #video
- Accuracy of a high-level, loss-tolerant video fingerprint for surveillance authentication (Y(R, LO), pp. 1088–1091.
- KDD-2012-BriggsFR
- Rank-loss support instance machines for MIML instance annotation (FB, XZF, RR), pp. 534–542.
- CASE-2011-TranHN #automation #composition
- Semi-automatic control of modular systems with intermittent data losses (TT, QPH, HTN), pp. 625–630.
- DAC-2011-TsengGS #comprehension #memory management
- Understanding the impact of power loss on flash memory (HWT, LMG, SS), pp. 35–40.
- DATE-2011-JhaLMR #simulation #statistics #trade-off #verification
- When to stop verification?: Statistical trade-off between expected loss and simulation cost (SKJ, CJL, SM, SR), pp. 1309–1314.
- HCD-2011-DasFS #requirements
- Management of Weight-Loss: Patients’ and Healthcare Professionals’ Requirements for an E-health System for Patients (AD, AF, DS), pp. 285–294.
- ICML-2011-BradleyKBG #coordination #parallel
- Parallel Coordinate Descent for L1-Regularized Loss Minimization (JKB, AK, DB, CG), pp. 321–328.
- ICML-2011-BuffoniCGU #learning #standard
- Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision (DB, CC, PG, NU), pp. 825–832.
- ICML-2011-GaoK #multi
- Multiclass Boosting with Hinge Loss based on Output Coding (TG, DK), pp. 569–576.
- ICML-2011-KotlowskiDH #ranking
- Bipartite Ranking through Minimization of Univariate Loss (WK, KD, EH), pp. 1113–1120.
- ICML-2011-NorouziF
- Minimal Loss Hashing for Compact Binary Codes (MN, DJF), pp. 353–360.
- ICML-2011-Scott #bound #classification
- Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs (CS), pp. 153–160.
- ECMFA-2011-GreenyerPR #incremental #reuse
- Preventing Information Loss in Incremental Model Synchronization by Reusing Elements (JG, SP, JR), pp. 144–159.
- OOPSLA-2011-WuHIN #java #performance #scalability
- Reducing trace selection footprint for large-scale Java applications without performance loss (PW, HH, HI, TN), pp. 789–804.
- STOC-2010-ChandranKOR #privacy
- Privacy amplification with asymptotically optimal entropy loss (NC, BK, RO, LR), pp. 785–794.
- CIKM-2010-LiLBZ #optimisation #ranking #web
- Optimizing unified loss for web ranking specialization (FL, XL, JB, ZZ), pp. 1593–1596.
- ICML-2010-MeshiSJG #approximate #learning
- Learning Efficiently with Approximate Inference via Dual Losses (OM, DS, TSJ, AG), pp. 783–790.
- ICML-2010-ZhangS #reduction
- Projection Penalties: Dimension Reduction without Loss (YZ, JGS), pp. 1223–1230.
- SIGIR-2010-LongCZCZT #learning #optimisation #ranking
- Active learning for ranking through expected loss optimization (BL, OC, YZ, YC, ZZ, BLT), pp. 267–274.
- CASE-2009-BukkapatnamMKSK #monitoring #realtime #using
- Real-time monitoring of container stability loss using wireless vibration sensor tags (STSB, SM, JK, VS, RK), pp. 221–226.
- DATE-2009-ChenW #3d #modelling #simulation
- New simulation methodology of 3D surface roughness loss for interconnects modeling (QC, NW), pp. 1184–1189.
- VLDB-2009-MozafariZ #classification #naive bayes #privacy
- Publishing Naive Bayesian Classifiers: Privacy without Accuracy Loss (BM, CZ), pp. 1173–1185.
- ICPC-2009-FeilkasRJ #architecture #case study #evolution #industrial
- The loss of architectural knowledge during system evolution: An industrial case study (MF, DR, EJ), pp. 188–197.
- ICEIS-AIDSS-2009-BiscarriMLGBM #detection #framework #mining
- A Mining Framework to Detect Non-technical Losses in Power Utilities (FB, IM, CL, JIG, JB, RM), pp. 96–101.
- ICML-2009-ReidW #bound
- Surrogate regret bounds for proper losses (MDR, RCW), pp. 897–904.
- ICML-2009-Shalev-ShwartzT #probability
- Stochastic methods for l1 regularized loss minimization (SSS, AT), pp. 929–936.
- CASE-2008-BiasiSLI #network #process #simulation
- Simulation of process control with WirelessHART networks subject to packet losses (MDB, CS, KL, AJI), pp. 548–553.
- DATE-2008-BingesserLHHMDV #metric
- Low-Noise Sigma-Delta Capacitance-to-Digital Converter for Sub-pF Capacitive Sensors with Integrated Dielectric Loss Measurement (MB, TL, WH, JH, SM, RD, MV), pp. 868–872.
- ICML-2008-DonmezC #learning #optimisation #rank #reduction
- Optimizing estimated loss reduction for active sampling in rank learning (PD, JGC), pp. 248–255.
- ICPR-2008-JinLH #learning #prototype
- Prototype learning with margin-based conditional log-likelihood loss (XJ, CLL, XH), pp. 1–4.
- KDD-2008-ChakrabartiKSB #learning #ranking
- Structured learning for non-smooth ranking losses (SC, RK, US, CB), pp. 88–96.
- KDD-2008-LozanoA #multi
- Multi-class cost-sensitive boosting with p-norm loss functions (ACL, NA), pp. 506–514.
- SAC-2008-FahmyRJ #realtime #scheduling #thread
- Scheduling distributable real-time threads in the presence of crash failures and message losses (SFF, BR, EDJ), pp. 294–301.
- CASE-2007-JinBS #approach
- A Consolidated Approach to Minimize Semiconductor Production Loss Due to Unscheduled ATE Downtime (TJ, FB, CHS), pp. 188–193.
- CASE-2007-MorrisonM #clustering #on the #throughput #tool support
- On the Throughput of Clustered Photolithography Tools: Wafer Advancement and Intrinsic Equipment Loss (JRM, MKM), pp. 88–93.
- VLDB-2007-GhinitaKKM #performance
- Fast Data Anonymization with Low Information Loss (GG, PK, PK, NM), pp. 758–769.
- HIMI-MTT-2007-ChoBKC #difference #on the #probability #using
- On Achieving Proportional Loss Differentiation Using Dynamic-MQDDP with Differential Drop Probability (KC, SB, JK, JWC), pp. 584–593.
- MLDM-2007-GrimH #analysis #category theory #clustering
- Minimum Information Loss Cluster Analysis for Categorical Data (JG, JH), pp. 233–247.
- SIGIR-2007-TsaiLQCM #named #ranking
- FRank: a ranking method with fidelity loss (MFT, TYL, TQ, HHC, WYM), pp. 383–390.
- SAC-2007-XianhuaJX #performance #reduction
- Efficient code size reduction without performance loss (LX, ZJ, CX), pp. 666–672.
- CASE-2006-ChenZY #multi #quality #research
- Research of Multi-operation Quality Control based on Minimum Quality Loss (CC, LZ, YY), pp. 437–441.
- DATE-2006-BudnikR #distributed #network #novel #power management #using
- Minimizing ohmic loss and supply voltage variation using a novel distributed power supply network (MMB, KR), pp. 1116–1121.
- DATE-2006-ChaoWCWC #using
- Coverage loss by using space compactors in presence of unknown values (MCTC, SW, STC, WW, KTC), pp. 1053–1054.
- SIGIR-2005-VriesR #question
- Relevance information: a loss of entropy but a gain for IDF? (APdV, TR), pp. 282–289.
- ICPR-v2-2004-GutierrezRA #identification
- Weighted Loss Functions to Make Risk-based Language Identification Fused Decisions (JG, JLR, RAO), pp. 863–866.
- SAC-2004-SeigneurJ #privacy #trust #ubiquitous
- Trust enhanced ubiquitous payment without too much privacy loss (JMS, CDJ), pp. 1593–1599.
- WCRE-2003-AndritsosT #clustering
- Software Clustering based on Information Loss Minimization (PA, VT), pp. 334–344.
- ICML-2003-ConitzerS03a #bound #framework #game studies #named
- BL-WoLF: A Framework For Loss-Bounded Learnability In Zero-Sum Games (VC, TS), pp. 91–98.
- ICML-2003-LiY #analysis #categorisation #classification
- A Loss Function Analysis for Classification Methods in Text Categorization (FL, YY), pp. 472–479.
- ICML-2002-GoebelRB #composition #performance #predict
- A Unified Decomposition of Ensemble Loss for Predicting Ensemble Performance (MG, PJR, MB), pp. 211–218.
- ASE-2001-FahmyHC #algebra #architecture
- Wins and Losses of Algebraic Transformations of Software Architectures (HF, RCH, JRC), pp. 51–62.
- STOC-2001-Ta-ShmaUZ
- Loss-less condensers, unbalanced expanders, and extractors (ATS, CU, DZ), pp. 143–152.
- ICML-2001-ChuKO #framework
- A Unified Loss Function in Bayesian Framework for Support Vector Regression (WC, SSK, CJO), pp. 51–58.
- ICML-2001-Hutter #bound #predict #sequence
- General Loss Bounds for Universal Sequence Prediction (MH), pp. 210–217.
- ICML-2000-ForsterW #bound #learning
- Relative Loss Bounds for Temporal-Difference Learning (JF, MKW), pp. 295–302.
- ICPR-1998-YogesanEB #analysis #image
- Texture analysis of retinal images to determine nerve fibre loss (KY, RHE, CJB), pp. 1665–1667.
- EDTC-1997-GavrilovGRBJV #performance
- Fast power loss calculation for digital static CMOS circuits (SG, AG, SR, DB, LGJ, GV), pp. 411–415.
- STOC-1997-LubyMSSS
- Practical Loss-Resilient Codes (ML, MM, MAS, DAS, VS), pp. 150–159.
- ICML-1996-KahaviW #bias #composition
- Bias Plus Variance Decomposition for Zero-One Loss Functions (RK, DW), pp. 275–283.
- SIGMOD-1992-Bamford #consistency #multi #performance #using
- Using Multiversioning to Improve Performance Without Loss of Consistency (RB), p. 164.
- VLDB-1989-BhargavaG #database
- Achieving Zero Information-Loss in a Classical Database Environment (GB, SKG), pp. 217–224.