| 2020 | AAAI | Proximity Preserving Binary Code Using Signed Graph-Cut. | Inbal Lavi, Shai Avidan, Yoram Singer, Yacov Hel-Or |
| 2020 | ALT | Exponentiated Gradient Meets Gradient Descent. | Udaya Ghai, Elad Hazan, Yoram Singer |
| 2020 | ICLR | Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. | Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer |
| 2018 | ICLR | Learning a neural response metric for retinal prosthesis. | Nishal P. Shah, Sasidhar Madugula, E. J. Chichilnisky, Yoram Singer, Jonathon Shlens |
| 2018 | ICML | Shampoo: Preconditioned Stochastic Tensor Optimization. | Vineet Gupta, Tomer Koren, Yoram Singer |
| 2018 | ICML | The Well-Tempered Lasso. | Yuanzhi Li, Yoram Singer |
| 2017 | ICLR | Short and Deep: Sketching and Neural Networks. | Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar |
| 2016 | ICML | Train faster, generalize better: Stability of stochastic gradient descent. | Moritz Hardt, Ben Recht, Yoram Singer |
| 2014 | WWW | Local collaborative ranking. | Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon, Yoram Singer |
| 2013 | ICML | Local Low-Rank Matrix Approximation. | Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer |
| 2011 | EMNLP | Entire Relaxation Path for Maximum Entropy Problems. | Moshe Dubiner, Yoram Singer |
| 2010 | COLT | Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. | John C. Duchi, Elad Hazan, Yoram Singer |
| 2010 | COLT | Composite Objective Mirror Descent. | John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari |
| 2009 | ICML | Boosting with structural sparsity. | John C. Duchi, Yoram Singer |
| 2008 | COLT | On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms. | Shai Shalev-Shwartz, Yoram Singer |
| 2008 | ICML | Efficient projections onto the | John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra |
| 2007 | ICCV | Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. | Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik |
| 2007 | ICML | Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. | Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro |
| 2006 | COLT | Online Multitask Learning. | Ofer Dekel, Philip M. Long, Yoram Singer |
| 2006 | COLT | Online Learning Meets Optimization in the Dual. | Shai Shalev-Shwartz, Yoram Singer |
| 2006 | ICML | Online multiclass learning by interclass hypothesis sharing. | Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman |
| 2006 | Interspeech | Discriminative kernel-based phoneme sequence recognition. | Joseph Keshet, Shai Shalev-Shwartz, Samy Bengio, Yoram Singer, Dan Chazan |
| 2005 | COLT | Loss Bounds for Online Category Ranking. | Koby Crammer, Yoram Singer |
| 2005 | COLT | A New Perspective on an Old Perceptron Algorithm. | Shai Shalev-Shwartz, Yoram Singer |
| 2005 | Interspeech | Phoneme alignment based on discriminative learning. | Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Dan Chazan |
| 2004 | ICML | Large margin hierarchical classification. | Ofer Dekel, Joseph Keshet, Yoram Singer |
| 2004 | ICML | Leveraging the margin more carefully. | Nir Krause, Yoram Singer |
| 2004 | ICML | Online and batch learning of pseudo-metrics. | Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng |
| 2003 | COLT | Learning Algorithm for Enclosing Points in Bregmanian Spheres. | Koby Crammer, Yoram Singer |
| 2003 | COLT | Smooth e-Intensive Regression by Loss Symmetrization. | Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer |
| 2003 | NAACL | Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. | Kristina Toutanova, Dan Klein, Christopher D. Manning, Yoram Singer |
| 2002 | ALT | An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. | Sanjoy Dasgupta, Elan Pavlov, Yoram Singer |
| 2002 | SIGIR | A new family of online algorithms for category ranking. | Koby Crammer, Yoram Singer |
| 2002 | SIGIR | Robust temporal and spectral modeling for query By melody. | Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer |
| 2001 | COLT | Ultraconservative Online Algorithms for Multiclass Problems. | Koby Crammer, Yoram Singer |
| 2001 | ISMB | Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences. | Eleazar Eskin, William Noble Grundy, Yoram Singer |
| 2000 | CIKM | Boosting for Document Routing. | Raj D. Iyer, David D. Lewis, Robert E. Schapire, Yoram Singer, Amit Singhal |
| 2000 | COLT | Logistic Regression, AdaBoost and Bregman Distances. | Michael Collins, Robert E. Schapire, Yoram Singer |
| 2000 | COLT | On the Learnability and Design of Output Codes for Multiclass Problems. | Koby Crammer, Yoram Singer |
| 2000 | ICML | Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. | Erin L. Allwein, Robert E. Schapire, Yoram Singer |
| 2000 | ICML | State-based Classification of Finger Gestures from Electromyographic Signals. | Peter Ju, Leslie Pack Kaelbling, Yoram Singer |
| 2000 | ISMB | Protein Family Classification Using Sparse Markov Transducers. | Eleazar Eskin, William Noble Grundy, Yoram Singer |
| 1999 | AAAI | A Simple, Fast, and Effictive Rule Learner. | William W. Cohen, Yoram Singer |
| 1999 | EMNLP | Boosting Applied to Tagging and PP Attachment. | Steven Abney, Robert E. Schapire, Yoram Singer |
| 1999 | EMNLP | Unsupervised Models for Named Entity Classification. | Michael Collins, Yoram Singer |
| 1998 | COLT | Improved Boosting Algorithms using Confidence-Rated Predictions. | Robert E. Schapire, Yoram Singer |
| 1998 | ICML | An Efficient Boosting Algorithm for Combining Preferences. | Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer |
| 1998 | SIGIR | Boosting and Rocchio Applied to Text Filtering. | Robert E. Schapire, Yoram Singer, Amit Singhal |
| 1998 | UAI | Switching Portfolios. | Yoram Singer |
| 1997 | COLT | An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. | Fernando C. N. Pereira, Yoram Singer |
| 1997 | STOC | Using and Combining Predictors That Specialize. | Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth |
| 1997 | UAI | Update Rules for Parameter Estimation in Bayesian Networks. | Eric Bauer, Daphne Koller, Yoram Singer |
| 1996 | ICML | On-Line Portfolio Selection Using Multiplicative Updates. | David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth |
| 1996 | SIGIR | Context-sensitive Learning Methods for Text Categorization. | William W. Cohen, Yoram Singer |
| 1995 | COLT | A Comparison of New and Old Algorithms for a Mixture Estimation Problem. | David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth |
| 1995 | COLT | On the Learnability and Usage of Acyclic Probabilistic Finite Automata. | Dana Ron, Yoram Singer, Naftali Tishby |
| 1994 | ACL | Part-of-Speech Tagging using a Variable Memory Markov Model. | Hinrich Schtze, Yoram Singer |
| 1994 | COLT | Learning Probabilistic Automata with Variable Memory Length. | Dana Ron, Yoram Singer, Naftali Tishby |
| 1993 | CVPR | Dynamical encoding of cursive handwriting. | Yoram Singer, Naftali Tishby |
| 1992 | ICPR | Learning class probabilities from labeled data. | Yoram Singer, Eyal Yair |