Learning class probabilities from labeled data. - Yoram Singer; Eyal Yair (ICPR (2), 1992)

The Power of Amnesia. - Dana Ron; Yoram Singer; Naftali Tishby (NIPS, 1993)

Decoding Cursive Scripts. - Yoram Singer; Naftali Tishby (NIPS, 1993)

Part-of-Speech Tagging using a Variable Memory Markov Model. - Hinrich Schütze; Yoram Singer (ACL, 1994)

Learning Probabilistic Automata with Variable Memory Length. - Dana Ron; Yoram Singer; Naftali Tishby (COLT, 1994)

Dynamical encoding of cursive handwriting. - Yoram Singer; Naftali Tishby (Biol. Cybern., 1994)

Beyond Word N-Grams. - Fernando Pereira 003; Yoram Singer; Naftali Tishby (VLC@ACL, 1995)

Adaptive Mixture of Probabilistic Transducers. - Yoram Singer (NIPS, 1995)

"What has been will be again": a machine learning approach to the analysis of natural language. - Yoram Singer (1995)

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

Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. - Yoram Singer; Manfred K. Warmuth (NIPS, 1996)

The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length. - Dana Ron; Yoram Singer; Naftali Tishby (Mach. Learn., 1996)

Shared Context Probabilistic Transducers. - Yoshua Bengio; Samy Bengio; Jean-Franc Isabelle; Yoram Singer (NIPS, 1997)

Using and Combining Predictors That Specialize. - Yoav Freund; Robert E. Schapire; Yoram Singer; Manfred K. Warmuth (STOC, 1997)

Update Rules for Parameter Estimation in Bayesian Networks. - Eric Bauer; Daphne Koller; Yoram Singer (UAI, 1997)

Switching Portfolios. - Yoram Singer (Int. J. Neural Syst., 1997)

A Comparison of New and Old Algorithms for a Mixture Estimation Problem. - David P. Helmbold; Robert E. Schapire; Yoram Singer; Manfred K. Warmuth (Mach. Learn., 1997)

Adaptive Mixtures of Probabilistic Transducers. - Yoram Singer (Neural Comput., 1997)

Efficient Bayesian Parameter Estimation in Large Discrete Domains. - Nir Friedman; Yoram Singer (NIPS, 1998)

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

Boosting and Rocchio Applied to Text Filtering. - Robert E. Schapire; Yoram Singer; Amit Singhal 001 (SIGIR, 1998)

On the Learnability and Usage of Acyclic Probabilistic Finite Automata. - Dana Ron; Yoram Singer; Naftali Tishby (J. Comput. Syst. Sci., 1998)

The Hierarchical Hidden Markov Model: Analysis and Applications. - Shai Fine; Yoram Singer; Naftali Tishby (Mach. Learn., 1998)

A Simple, Fast, and Effictive Rule Learner. - William W. Cohen; Yoram Singer (AAAI/IAAI, 1999)

Boosting Applied to Tagging and PP Attachment. - Steven Abney; Robert E. Schapire; Yoram Singer (EMNLP, 1999)

Unsupervised Models for Named Entity Classification. - Michael Collins 001; Yoram Singer (EMNLP, 1999)

Leveraged Vector Machines. - Yoram Singer (NIPS, 1999)

Learning to Order Things. - William W. Cohen; Robert E. Schapire; Yoram Singer (J. Artif. Intell. Res., 1999)

An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. - Fernando C. N. Pereira; Yoram Singer (Mach. Learn., 1999)

Improved Boosting Algorithms Using Confidence-rated Predictions. - Robert E. Schapire; Yoram Singer (Mach. Learn., 1999)

Context-Sensitive Learning Methods for Text Categorization. - William W. Cohen; Yoram Singer (ACM Trans. Inf. Syst., 1999)

Boosting for Document Routing. - Raj D. Iyer; David D. Lewis; Robert E. Schapire; Yoram Singer; Amit Singhal 001 (CIKM, 2000)

State-based Classification of Finger Gestures from Electromyographic Signals. - Peter Ju; Leslie Pack Kaelbling; Yoram Singer (ICML, 2000)

Improved Output Coding for Classification Using Continuous Relaxation. - Koby Crammer; Yoram Singer (NIPS, 2000)

Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. - Erin L. Allwein; Robert E. Schapire; Yoram Singer (J. Mach. Learn. Res., 2000)

BoosTexter: A Boosting-based System for Text Categorization. - Robert E. Schapire; Yoram Singer (Mach. Learn., 2000)

Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences. - Eleazar Eskin; William Noble Grundy; Yoram Singer (ISMB (Supplement of Bioinformatics), 2001)

Pranking with Ranking. - Koby Crammer; Yoram Singer (NIPS, 2001)

On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. - Koby Crammer; Yoram Singer (J. Mach. Learn. Res., 2001)

Guest Editor's Introduction. - Yoram Singer (Mach. Learn., 2001)

An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. - Sanjoy Dasgupta; Elan Pavlov; Yoram Singer (ALT, 2002)

Discriminative Binaural Sound Localization. - Ehud Ben-Reuven; Yoram Singer (NIPS, 2002)

Kernel Design Using Boosting. - Koby Crammer; Joseph Keshet; Yoram Singer (NIPS, 2002)

Multiclass Learning by Probabilistic Embeddings. - Ofer Dekel; Yoram Singer (NIPS, 2002)

Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. - Lavi Shpigelman; Yoram Singer; Rony Paz; Eilon Vaadia (NIPS, 2002)

A new family of online algorithms for category ranking. - Koby Crammer; Yoram Singer (SIGIR, 2002)

Robust temporal and spectral modeling for query By melody. - Shai Shalev-Shwartz; Shlomo Dubnov; Nir Friedman; Yoram Singer (SIGIR, 2002)

Using Substitution Matrices to Estimate Probability Distributions for Biological Sequences. - Eleazar Eskin; William Stafford Noble; Yoram Singer (J. Comput. Biol., 2002)

Logistic Regression, AdaBoost and Bregman Distances. - Michael Collins 001; Robert E. Schapire; Yoram Singer (Mach. Learn., 2002)

On the Learnability and Design of Output Codes for Multiclass Problems. - Koby Crammer; Yoram Singer (Mach. Learn., 2002)

Learning Algorithm for Enclosing Points in Bregmanian Spheres. - Koby Crammer; Yoram Singer (COLT, 2003)

Smooth e-Intensive Regression by Loss Symmetrization. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (COLT, 2003)

Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. - Kristina Toutanova; Dan Klein 001; Christopher D. Manning; Yoram Singer (HLT-NAACL, 2003)

Online Classification on a Budget. - Koby Crammer; Jaz S. Kandola; Yoram Singer (NIPS, 2003)

Log-Linear Models for Label Ranking. - Ofer Dekel; Christopher D. Manning; Yoram Singer (NIPS, 2003)

Online Passive-Aggressive Algorithms. - Shai Shalev-Shwartz; Koby Crammer; Ofer Dekel; Yoram Singer (NIPS, 2003)

Protein Family Classification Using Sparse Markov Transducers. - Eleazar Eskin; William Stafford Noble; Yoram Singer (J. Comput. Biol., 2003)

Ultraconservative Online Algorithms for Multiclass Problems. - Koby Crammer; Yoram Singer (J. Mach. Learn. Res., 2003)

A Family of Additive Online Algorithms for Category Ranking. - Koby Crammer; Yoram Singer (J. Mach. Learn. Res., 2003)

An Efficient Boosting Algorithm for Combining Preferences. - Yoav Freund; Raj D. Iyer; Robert E. Schapire; Yoram Singer (J. Mach. Learn. Res., 2003)

Large margin hierarchical classification. - Ofer Dekel; Joseph Keshet; 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 (ICML, 2004)

Learning to Align Polyphonic Music. - Shai Shalev-Shwartz; Joseph Keshet; Yoram Singer (ISMIR, 2004)

An Online Algorithm for Hierarchical Phoneme Classification. - Ofer Dekel; Joseph Keshet; Yoram Singer (MLMI, 2004)

The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (NIPS, 2004)

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

Loss Bounds for Online Category Ranking. - Koby Crammer; Yoram Singer (COLT, 2005)

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

Phoneme alignment based on discriminative learning. - Joseph Keshet; Shai Shalev-Shwartz; Yoram Singer; Dan Chazan (INTERSPEECH, 2005)

Data-Driven Online to Batch Conversions. - Ofer Dekel; Yoram Singer (NIPS, 2005)

The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (NIPS, 2005)

Smooth epsiloon-Insensitive Regression by Loss Symmetrization. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2005)

Online Ranking by Projecting. - Koby Crammer; Yoram Singer (Neural Comput., 2005)

Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces. - Lavi Shpigelman; Yoram Singer; Rony Paz; Eilon Vaadia (Neural Comput., 2005)

Online Multitask Learning. - Ofer Dekel; Philip M. Long; Yoram Singer (COLT, 2006)

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

Online multiclass learning by interclass hypothesis sharing. - Michael Fink 002; Shai Shalev-Shwartz; Yoram Singer; Shimon Ullman (ICML, 2006)

Discriminative kernel-based phoneme sequence recognition. - Joseph Keshet; Shai Shalev-Shwartz; Samy Bengio; Yoram Singer; Dan Chazan (INTERSPEECH, 2006)

Online Classification for Complex Problems Using Simultaneous Projections. - Yonatan Amit; Shai Shalev-Shwartz; Yoram Singer (NIPS, 2006)

Support Vector Machines on a Budget. - Ofer Dekel; Yoram Singer (NIPS, 2006)

Image Retrieval and Classification Using Local Distance Functions. - Andrea Frome; Yoram Singer; Jitendra Malik (NIPS, 2006)

Convex Repeated Games and Fenchel Duality. - Shai Shalev-Shwartz; Yoram Singer (NIPS, 2006)

Online Passive-Aggressive Algorithms. - Koby Crammer; Ofer Dekel; Joseph Keshet; Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2006)

Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. - Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2006)

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

Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. - Shai Shalev-Shwartz; Yoram Singer; Nathan Srebro (ICML, 2007)

A Boosting Algorithm for Label Covering in Multilabel Problems. - Yonatan Amit; Ofer Dekel; Yoram Singer (AISTATS, 2007)

Online Learning of Multiple Tasks with a Shared Loss. - Ofer Dekel; Philip M. Long; Yoram Singer (J. Mach. Learn. Res., 2007)

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

A primal-dual perspective of online learning algorithms. - Shai Shalev-Shwartz; Yoram Singer (Mach. Learn., 2007)

A Large Margin Algorithm for Speech-to-Phoneme and Music-to-Score Alignment. - Joseph Keshet; Shai Shalev-Shwartz; Yoram Singer; Dan Chazan (IEEE Trans. Speech Audio Process., 2007)

Efficient projections onto the l1-ball for learning in high dimensions. - John C. Duchi; Shai Shalev-Shwartz; Yoram Singer; Tushar Chandra (ICML, 2008)

Online Learning of Complex Prediction Problems Using Simultaneous Projections. - Yonatan Amit; Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2008)

The Forgetron: A Kernel-Based Perceptron on a Budget. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (SIAM J. Comput., 2008)

Boosting with structural sparsity. - John C. Duchi; Yoram Singer (ICML, 2009)

Group Sparse Coding. - Samy Bengio; Fernando C. N. Pereira; Yoram Singer; Dennis Strelow (NIPS, 2009)

Efficient Learning using Forward-Backward Splitting. - John C. Duchi; Yoram Singer (NIPS, 2009)

Efficient Online and Batch Learning Using Forward Backward Splitting. - John C. Duchi; Yoram Singer (J. Mach. Learn. Res., 2009)

Individual sequence prediction using memory-efficient context trees. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (IEEE Trans. Inf. Theory, 2009)

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

On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms. - Shai Shalev-Shwartz; Yoram Singer (Mach. Learn., 2010)

Entire Relaxation Path for Maximum Entropy Problems. - Moshe Dubiner; Yoram Singer (EMNLP, 2011)

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. - John C. Duchi; Elad Hazan; Yoram Singer (J. Mach. Learn. Res., 2011)

Pegasos: primal estimated sub-gradient solver for SVM. - Shai Shalev-Shwartz; Yoram Singer; Nathan Srebro; Andrew Cotter (Math. Program., 2011)

Efficient Learning of Sparse Ranking Functions. - Mark Stevens; Samy Bengio; Yoram Singer (Empirical Inference, 2013)

Local Low-Rank Matrix Approximation. - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (ICML (2), 2013)

Parallel Boosting with Momentum. - Indraneel Mukherjee; Kevin Robert Canini; Rafael M. Frongillo; Yoram Singer (ECML/PKDD (3), 2013)

Using Web Co-occurrence Statistics for Improving Image Categorization. - Samy Bengio; Jeffrey Dean; Dumitru Erhan; Eugene Ie; Quoc V. Le; Andrew Rabinovich; Jonathon Shlens; Yoram Singer (CoRR, 2013)

The Maximum Entropy Relaxation Path. - Moshe Dubiner; Matan Gavish; Yoram Singer (CoRR, 2013)

Matrix Approximation under Local Low-Rank Assumption - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (ICLR (Workshop Poster), 2013)

Local collaborative ranking. - Joonseok Lee; Samy Bengio; Seungyeon Kim 001; Guy Lebanon; Yoram Singer (WWW, 2014)

Zero-Shot Learning by Convex Combination of Semantic Embeddings. - Mohammad Norouzi 002; Tomás Mikolov; Samy Bengio; Yoram Singer; Jonathon Shlens; Andrea Frome; Greg Corrado; Jeffrey Dean (ICLR, 2014)

Train faster, generalize better: Stability of stochastic gradient descent. - Moritz Hardt; Ben Recht; Yoram Singer (ICML, 2016)

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. - Amit Daniely; Roy Frostig; Yoram Singer (NIPS, 2016)

Sketching and Neural Networks. - Amit Daniely; Nevena Lazic; Yoram Singer; Kunal Talwar (CoRR, 2016)

LLORMA: Local Low-Rank Matrix Approximation. - Joonseok Lee; Seungyeon Kim 001; Guy Lebanon; Yoram Singer; Samy Bengio (J. Mach. Learn. Res., 2016)

A Stochastic Quasi-Newton Method for Large-Scale Optimization. - Richard H. Byrd; S. L. Hansen; Jorge Nocedal; Yoram Singer (SIAM J. Optim., 2016)

Short and Deep: Sketching and Neural Networks. - Amit Daniely; Nevena Lazic; Yoram Singer; Kunal Talwar (ICLR (Workshop), 2017)

Random Features for Compositional Kernels. - Amit Daniely; Roy Frostig; Vineet Gupta 001; Yoram Singer (CoRR, 2017)

A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization. - Vineet Gupta 001; Tomer Koren; Yoram Singer (CoRR, 2017)

Learning a neural response metric for retinal prosthesis. - Nishal P. Shah; Sasidhar Madugula; E. J. Chichilnisky; Yoram Singer; Jonathon Shlens (ICLR (Poster), 2018)

Shampoo: Preconditioned Stochastic Tensor Optimization. - Vineet Gupta 001; Tomer Koren; Yoram Singer (ICML, 2018)

The Well-Tempered Lasso. - Yuanzhi Li; Yoram Singer (ICML, 2018)

Memory Efficient Adaptive Optimization. - Rohan Anil; Vineet Gupta 001; Tomer Koren; Yoram Singer (NeurIPS, 2019)

Memory-Efficient Adaptive Optimization for Large-Scale Learning. - Rohan Anil; Vineet Gupta 001; Tomer Koren; Yoram Singer (CoRR, 2019)

Identity Crisis: Memorization and Generalization under Extreme Overparameterization. - Chiyuan Zhang; Samy Bengio; Moritz Hardt; Yoram Singer (CoRR, 2019)

Convolutional Bipartite Attractor Networks. - Michael L. Iuzzolino; Yoram Singer; Michael C. Mozer (CoRR, 2019)

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

Exponentiated Gradient Meets Gradient Descent. - Udaya Ghai; Elad Hazan; Yoram Singer (ALT, 2020)

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

Second Order Optimization Made Practical. - Rohan Anil; Vineet Gupta 001; Tomer Koren; Kevin Regan 001; Yoram Singer (CoRR, 2020)

Are All Layers Created Equal? - Chiyuan Zhang; Samy Bengio; Yoram Singer (J. Mach. Learn. Res., 2022)