Singer, Yoram

106 publications

JMLR 2022 Are All Layers Created Equal? Chiyuan Zhang, Samy Bengio, Yoram Singer

ALT 2020 Exponentiated Gradient Meets Gradient Descent Udaya Ghai, Elad Hazan, Yoram Singer

ICLR 2020 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer

AAAI 2020 Proximity Preserving Binary Code Using Signed Graph-Cut Inbal Lavi, Shai Avidan, Yoram Singer, Yacov Hel-Or

ICMLW 2019 Are All Layers Created Equal? Chiyuan Zhang, Samy Bengio, Yoram Singer

ICMLW 2019 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer

NeurIPS 2019 Memory Efficient Adaptive Optimization Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer

ICLR 2018 Learning a Neural Response Metric for Retinal Prosthesis Nishal P Shah, Sasidhar Madugula, Ej Chichilnisky, Yoram Singer, Jonathon Shlens

ICML 2018 Shampoo: Preconditioned Stochastic Tensor Optimization Vineet Gupta, Tomer Koren, Yoram Singer

ICML 2018 The Well-Tempered Lasso Yuanzhi Li, Yoram Singer

ICLR 2017 Short and Deep: Sketching and Neural Networks Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar

JMLR 2016 LLORMA: Local Low-Rank Matrix Approximation Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer, Samy Bengio

NeurIPS 2016 Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity Amit Daniely, Roy Frostig, Yoram Singer

ICML 2016 Train Faster, Generalize Better: Stability of Stochastic Gradient Descent Moritz Hardt, Ben Recht, Yoram Singer

ICLR 2014 Zero-Shot Learning by Convex Combination of Semantic Embeddings Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean

ICML 2013 Local Low-Rank Matrix Approximation Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer

ICLR 2013 Matrix Approximation Under Local Low-Rank Assumption Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer

ECML-PKDD 2013 Parallel Boosting with Momentum Indraneel Mukherjee, Kevin Robert Canini, Rafael M. Frongillo, Yoram Singer

JMLR 2011 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John Duchi, Elad Hazan, Yoram Singer

COLT 2010 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John C. Duchi, Elad Hazan, Yoram Singer

COLT 2010 Composite Objective Mirror Descent John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari

MLJ 2010 On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms Shai Shalev-Shwartz, Yoram Singer

ICML 2009 Boosting with Structural Sparsity John C. Duchi, Yoram Singer

NeurIPS 2009 Efficient Learning Using Forward-Backward Splitting Yoram Singer, John C. Duchi

JMLR 2009 Efficient Online and Batch Learning Using Forward Backward Splitting John Duchi, Yoram Singer

NeurIPS 2009 Group Sparse Coding Samy Bengio, Fernando Pereira, Yoram Singer, Dennis Strelow

ICML 2008 Efficient Projections onto the L1-Ball for Learning in High Dimensions John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra

COLT 2008 On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms Shai Shalev-Shwartz, Yoram Singer

JMLR 2008 Online Learning of Complex Prediction Problems Using Simultaneous Projections Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer

AISTATS 2007 A Boosting Algorithm for Label Covering in Multilabel Problems Yonatan Amit, Ofer Dekel, Yoram Singer

MLJ 2007 A Primal-Dual Perspective of Online Learning Algorithms Shai Shalev-Shwartz, Yoram Singer

AISTATS 2007 A Unified Algorithmic Approach for Efficient Online Label Ranking Shai Shalev-Shwartz, Yoram Singer

ICCV 2007 Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik

JMLR 2007 Online Learning of Multiple Tasks with a Shared Loss Ofer Dekel, Philip M. Long, Yoram Singer

ICML 2007 Pegasos: Primal Estimated Sub-GrAdient SOlver for SVM Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro

NeurIPS 2006 Convex Repeated Games and Fenchel Duality Shai Shalev-shwartz, Yoram Singer

JMLR 2006 Efficient Learning of Label Ranking by Soft Projections onto Polyhedra Shai Shalev-Shwartz, Yoram Singer

NeurIPS 2006 Image Retrieval and Classification Using Local Distance Functions Andrea Frome, Yoram Singer, Jitendra Malik

NeurIPS 2006 Online Classification for Complex Problems Using Simultaneous Projections Yonatan Amit, Shai Shalev-shwartz, Yoram Singer

COLT 2006 Online Learning Meets Optimization in the Dual Shai Shalev-Shwartz, Yoram Singer

ICML 2006 Online Multiclass Learning by Interclass Hypothesis Sharing Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman

COLT 2006 Online Multitask Learning Ofer Dekel, Philip M. Long, Yoram Singer

JMLR 2006 Online Passive-Aggressive Algorithms Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer

NeurIPS 2006 Support Vector Machines on a Budget Ofer Dekel, Yoram Singer

COLT 2005 A New Perspective on an Old Perceptron Algorithm Shai Shalev-Shwartz, Yoram Singer

NeurIPS 2005 Data-Driven Online to Batch Conversions Ofer Dekel, Yoram Singer

COLT 2005 Loss Bounds for Online Category Ranking Koby Crammer, Yoram Singer

JMLR 2005 Smooth Ε-Insensitive Regression by Loss Symmetrization Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer

NeurIPS 2005 The Forgetron: A Kernel-Based Perceptron on a Fixed Budget Ofer Dekel, Shai Shalev-shwartz, Yoram Singer

NeurIPS 2004 A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer

ICML 2004 Large Margin Hierarchical Classification Ofer Dekel, Joseph Keshet, Yoram Singer

COLT 2004 Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings John Shawe-Taylor, Yoram Singer

ICML 2004 Leveraging the Margin More Carefully Nir Krause, Yoram Singer

ICML 2004 Online and Batch Learning of Pseudo-Metrics Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng

NeurIPS 2004 The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees Ofer Dekel, Shai Shalev-shwartz, Yoram Singer

JMLR 2003 An Efficient Boosting Algorithm for Combining Preferences Yoav Freund, Raj Iyer, Robert E. Schapire, Yoram Singer

COLT 2003 Learning Algorithm for Enclosing Points in Bregmanian Spheres Koby Crammer, Yoram Singer

NeurIPS 2003 Log-Linear Models for Label Ranking Ofer Dekel, Yoram Singer, Christopher D. Manning

NeurIPS 2003 Online Classification on a Budget Koby Crammer, Jaz Kandola, Yoram Singer

NeurIPS 2003 Online Passive-Aggressive Algorithms Shai Shalev-shwartz, Koby Crammer, Ofer Dekel, Yoram Singer

COLT 2003 Smooth E-Intensive Regression by Loss Symmetrization Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer

ALT 2002 An Efficient PAC Algorithm for Reconstructing a Mixture of Lines Sanjoy Dasgupta, Elan Pavlov, Yoram Singer

NeurIPS 2002 Discriminative Binaural Sound Localization Ehud Ben-reuven, Yoram Singer

NeurIPS 2002 Kernel Design Using Boosting Koby Crammer, Joseph Keshet, Yoram Singer

MLJ 2002 Logistic Regression, AdaBoost and Bregman Distances Michael Collins, Robert E. Schapire, Yoram Singer

NeurIPS 2002 Multiclass Learning by Probabilistic Embeddings Ofer Dekel, Yoram Singer

MLJ 2002 On the Learnability and Design of Output Codes for Multiclass Problems Koby Crammer, Yoram Singer

NeurIPS 2002 Spikernels: Embedding Spiking Neurons in Inner-Product Spaces Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia

MLJ 2001 Guest Editor's Introduction Yoram Singer

JMLR 2001 On the Algorithmic Implementation of Multiclass Kernel-Based Vector Machines (Kernel Machines Section) Koby Crammer, Yoram Singer

NeurIPS 2001 Pranking with Ranking Koby Crammer, Yoram Singer

COLT 2001 Ultraconservative Online Algorithms for Multiclass Problems Koby Crammer, Yoram Singer

MLJ 2000 BoosTexter: A Boosting-Based System for Text Categorization Robert E. Schapire, Yoram Singer

NeurIPS 2000 Improved Output Coding for Classification Using Continuous Relaxation Koby Crammer, Yoram Singer

COLT 2000 Logistic Regression, AdaBoost and Bregman Distances Michael Collins, Robert E. Schapire, Yoram Singer

COLT 2000 On the Learnability and Design of Output Codes for Multiclass Problems Koby Crammer, Yoram Singer

JMLR 2000 Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers Erin L. Allwein, Robert E. Schapire, Yoram Singer

ICML 2000 Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers Erin L. Allwein, Robert E. Schapire, Yoram Singer

ICML 2000 State-Based Classification of Finger Gestures from Electromyographic Signals Peter Ju, Leslie Pack Kaelbling, Yoram Singer

AAAI 1999 A Simple, Fast, and Effictive Rule Learner William W. Cohen, Yoram Singer

MLJ 1999 An Efficient Extension to Mixture Techniques for Prediction and Decision Trees Fernando C. N. Pereira, Yoram Singer

MLJ 1999 Improved Boosting Algorithms Using Confidence-Rated Predictions Robert E. Schapire, Yoram Singer

JAIR 1999 Learning to Order Things William W. Cohen, Robert E. Schapire, Yoram Singer

NeurIPS 1999 Leveraged Vector Machines Yoram Singer

ICML 1998 An Efficient Boosting Algorithm for Combining Preferences Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer

NeurIPS 1998 Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy Yoram Singer, Manfred K. Warmuth

NeurIPS 1998 Efficient Bayesian Parameter Estimation in Large Discrete Domains Nir Friedman, Yoram Singer

COLT 1998 Improved Boosting Algorithms Using Confidence-Rated Predictions Robert E. Schapire, Yoram Singer

UAI 1998 Switching Portfolios Yoram Singer

MLJ 1998 The Hierarchical Hidden Markov Model: Analysis and Applications Shai Fine, Yoram Singer, Naftali Tishby

MLJ 1997 A Comparison of New and Old Algorithms for a Mixture Estimation Problem David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth

NeCo 1997 Adaptive Mixtures of Probabilistic Transducers Yoram Singer

COLT 1997 An Efficient Extension to Mixture Techniques for Prediction and Decision Trees Fernando C. N. Pereira, Yoram Singer

NeurIPS 1997 Learning to Order Things William W. Cohen, Robert E. Schapire, Yoram Singer

NeurIPS 1997 Shared Context Probabilistic Transducers Yoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer

UAI 1997 Update Rules for Parameter Estimation in Bayesian Networks Eric Bauer, Daphne Koller, Yoram Singer

ICML 1996 On-Line Portfolio Selection Using Multiplicative Updates David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth

MLJ 1996 The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length Dana Ron, Yoram Singer, Naftali Tishby

NeurIPS 1996 Training Algorithms for Hidden Markov Models Using Entropy Based Distance Functions Yoram Singer, Manfred K. Warmuth

COLT 1995 A Comparison of New and Old Algorithms for a Mixture Estimation Problem David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth

NeurIPS 1995 Adaptive Mixture of Probabilistic Transducers Yoram Singer

COLT 1995 On the Learnability and Usage of Acyclic Probabilistic Finite Automata Dana Ron, Yoram Singer, Naftali Tishby

COLT 1994 Learning Probabilistic Automata with Variable Memory Length Dana Ron, Yoram Singer, Naftali Tishby

NeurIPS 1993 Decoding Cursive Scripts Yoram Singer, Naftali Tishby

CVPR 1993 Dynamical Encoding of Cursive Handwriting Yoram Singer, Naftali Tishby

NeurIPS 1993 The Power of Amnesia Dana Ron, Yoram Singer, Naftali Tishby