Y. Singer

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Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Yoram Singer, Elad Hazan, John C. Duchi, 2011, J. Mach. Learn. Res..

Logarithmic Regret Algorithms for Strongly Convex Repeated Games

Y. Singer, S. Shalev-Shwartz, 2007 .

Ultraconservative online algorithms for multiclass problems

Y. Singer, K. Crammer, 2003 .

A Comparison of New and Old Algorithms for a Mixture Estimation Problem

Yoram Singer, Manfred K. Warmuth, Robert E. Schapire, 2004, Machine Learning.

A Comparison of New and Old Algorithms for a Mixture Estimation Problem

Yoram Singer, Manfred K. Warmuth, Robert E. Schapire, 1995, COLT '95.

On‐Line Portfolio Selection Using Multiplicative Updates

Yoram Singer, Manfred K. Warmuth, Robert E. Schapire, 1998, ICML.

Train faster, generalize better: Stability of stochastic gradient descent pdf

Yoram Singer, Benjamin Recht, Moritz Hardt, 2015, ICML.

Pegasos: primal estimated sub-gradient solver for SVM

Yoram Singer, Nathan Srebro, Andrew Cotter, 2011, Math. Program..

Pegasos: primal estimated sub-gradient solver for SVM

Yoram Singer, Nathan Srebro, Shai Shalev-Shwartz, 2007, ICML '07.

Efficient Learning using Forward-Backward Splitting

Yoram Singer, John C. Duchi, Y. Singer, 2009, NIPS.

Convex Repeated Games and Fenchel Duality

Yoram Singer, Shai Shalev-Shwartz, Y. Singer, 2006, NIPS.

Online Learning Meets Optimization in the Dual

Yoram Singer, Shai Shalev-Shwartz, Y. Singer, 2006, COLT.

Online Passive-Aggressive Algorithms

Koby Crammer, Yoram Singer, Shai Shalev-Shwartz, 2003, J. Mach. Learn. Res..

Composite objective mirror descent

Ambuj Tewari, Yoram Singer, Shai Shalev-Shwartz, 2010, COLT 2010.

Efficient projections onto the l1-ball for learning in high dimensions

Yoram Singer, Shai Shalev-Shwartz, John C. Duchi, 2008, ICML '08.

Efficient Online and Batch Learning Using Forward Backward Splitting

Yoram Singer, John C. Duchi, Y. Singer, 2009, J. Mach. Learn. Res..

Using and combining predictors that specialize

Yoram Singer, Yoav Freund, Manfred K. Warmuth, 1997, STOC '97.

On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms

Yoram Singer, Shai Shalev-Shwartz, Y. Singer, 2010, Machine Learning.

A Stochastic Quasi-Newton Method for Large-Scale Optimization

Jorge Nocedal, Yoram Singer, Richard H. Byrd, 2014, SIAM J. Optim..

On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines

Koby Crammer, Yoram Singer, Y. Singer, 2002, J. Mach. Learn. Res..

Improved Boosting Algorithms Using Confidence-rated Predictions

Yoram Singer, Robert E. Schapire, R. Schapire, 1998, COLT' 98.

An Efficient Boosting Algorithm for Combining Preferences by

Yoram Singer, Yoav Freund, Robert E. Schapire, 2013 .

Context-sensitive learning methods for text categorization

Yoram Singer, William W. Cohen, Y. Singer, 1996, SIGIR '96.

Learning probabilistic automata with variable memory length

Dana Ron, Yoram Singer, Naftali Tishby, 1994, COLT '94.

Improved Boosting Algorithms Using Confidence-rated Predictions

Yoram Singer, Robert E. Schapire, R. Schapire, 1998, COLT' 98.

Logistic Regression, AdaBoost and Bregman Distances

Yoram Singer, Robert E. Schapire, Michael Collins, 2000, Machine Learning.

Image Retrieval and Classification Using Local Distance Functions

Jitendra Malik, Yoram Singer, Andrea Frome, 2006, NIPS.

The Power of Amnesia

Dana Ron, Yoram Singer, Naftali Tishby, 1993, NIPS.

Efficient Bayesian Parameter Estimation in Large Discrete Domains

Yoram Singer, Nir Friedman, Y. Singer, 1998, NIPS.

The power of amnesia: Learning probabilistic automata with variable memory length

Dana Ron, Yoram Singer, Naftali Tishby, 1996, Machine Learning.

Online and batch learning of pseudo-metrics

Yoram Singer, Andrew Y. Ng, Shai Shalev-Shwartz, 2004, ICML.

The Forgetron: A Kernel-Based Perceptron on a Fixed Budget

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2005, NIPS.

Switching Portfolios

Yoram Singer, Y. Singer, 1998, Int. J. Neural Syst..

On the Learnability and Design of Output Codes for Multiclass Problems

Koby Crammer, Yoram Singer, Y. Singer, 2002, Machine Learning.

BoosTexter: A Boosting-based System for Text Categorization

Yoram Singer, Robert E. Schapire, R. Schapire, 2000, Machine Learning.

Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification

Jitendra Malik, Yoram Singer, Fei Sha, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Zero-Shot Learning by Convex Combination of Semantic Embeddings

Samy Bengio, Yoram Singer, Mohammad Norouzi, 2013, ICLR.

Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers

Yoram Singer, Robert E. Schapire, Erin L. Allwein, 2000, J. Mach. Learn. Res..

A new family of online algorithms for category ranking

Koby Crammer, Yoram Singer, Y. Singer, 2002, SIGIR '02.

A primal-dual perspective of online learning algorithms

Yoram Singer, Shai Shalev-Shwartz, Y. Singer, 2007, Machine Learning.

Learning to Order Things pdf

Yoram Singer, William W. Cohen, Robert E. Schapire, 1997, NIPS.

The Forgetron: A Kernel-Based Perceptron on a Budget

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2008, SIAM J. Comput..

Ultraconservative Online Algorithms for Multiclass Problems

Koby Crammer, Yoram Singer, Y. Singer, 2001, J. Mach. Learn. Res..

Boosting and Rocchio applied to text filtering

Yoram Singer, Robert E. Schapire, Amit Singhal, 1998, SIGIR '98.

Pranking with Ranking

Koby Crammer, Yoram Singer, Y. Singer, 2001, NIPS.

The Hierarchical Hidden Markov Model: Analysis and Applications

Yoram Singer, Naftali Tishby, Shai Fine, 1998, Machine Learning.

Large margin hierarchical classification

Yoram Singer, Joseph Keshet, Ofer Dekel, 2004, ICML.

Update Rules for Parameter Estimation in Bayesian Networks

Eric Bauer, Yoram Singer, Daphne Koller, 1997, UAI.

Efficient projections onto the {\it l}$_{\mbox{1}}$-ball for learning in high dimensions

Yoram Singer, Shai Shalev-Shwartz, Tushar Deepak Chandra, 2008, International Conference on Machine Learning.

Advances in Neural Information Processing Systems 14

Koby Crammer, Yoram Singer, Y. Singer, 2002 .

Multiclass Learning by Probabilistic Embeddings

Yoram Singer, Ofer Dekel, Y. Singer, 2002, NIPS.

Local collaborative ranking

Samy Bengio, Yoram Singer, Guy Lebanon, 2014, WWW.

Adaptive Mixtures of Probabilistic Transducers

Yoram Singer, Y. Singer, 1995, Neural Computation.

Exponentiated Gradient Meets Gradient Descent

Yoram Singer, Elad Hazan, Udaya Ghai, 2019, 1902.01903.

Boosting for document routing

Yoram Singer, Robert E. Schapire, Amit Singhal, 2000, CIKM '00.

Shining Bright: The Golden Era of Signal Processing

Vikram Krishnamurthy, Brendan J. Frey, Holger Boche, 2011 .

On the learnability and usage of acyclic probabilistic finite automata

Dana Ron, Yoram Singer, Naftali Tishby, 1995, COLT '95.

Beyond Word N-Grams

Yoram Singer, Naftali Tishby, Fernando Pereira, 1996, VLC@ACL.

An Online Algorithm for Hierarchical Phoneme Classification

Yoram Singer, Joseph Keshet, Ofer Dekel, 2004, MLMI.

Learning to Query the Web

Yoram Singer, William W. Cohen, Y. Singer, 1996 .

Learning a neural response metric for retinal prosthesis

Yoram Singer, Jonathon Shlens, Nishal P. Shah, 2017, bioRxiv.

Kernel Design Using Boosting

Koby Crammer, Yoram Singer, Joseph Keshet, 2002, NIPS.

A Boosting Algorithm for Label Covering in Multilabel Problems

Yoram Singer, Ofer Dekel, Yonatan Amit, 2007, AISTATS.

Group Sparse Coding

Samy Bengio, Yoram Singer, Fernando Pereira, 2009, NIPS.

A Family of Additive Online Algorithms for Category Ranking

Koby Crammer, Yoram Singer, Y. Singer, 2003, J. Mach. Learn. Res..

Boosting with structural sparsity

Yoram Singer, John C. Duchi, Y. Singer, 2009, ICML '09.

Smooth e-Intensive Regression by Loss Symmetrization

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2005, COLT.

Smooth ε-insensitive regression by loss symmetrization

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2003, COLT 2003.

State-based Classification of Finger Gestures from Electromyographic Signals

Leslie Pack Kaelbling, Yoram Singer, Peter Ju, 2000, ICML.

Learning to Align Polyphonic Music

Yoram Singer, Shai Shalev-Shwartz, Joseph Keshet, 2004, ISMIR.

Discriminative Binaural Sound Localization

Yoram Singer, Ehud Ben-Reuven, Y. Singer, 2002, NIPS.

Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions

Yoram Singer, Manfred K. Warmuth, Y. Singer, 1996, NIPS.

Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences

Eleazar Eskin, William Noble Grundy, Yoram Singer, 2001, ISMB.

Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network

Dan Klein, Yoram Singer, Christopher D. Manning, 2003, NAACL.

Log-Linear Models for Label Ranking

Yoram Singer, Christopher D. Manning, Ofer Dekel, 2003, NIPS.

Individual Sequence Prediction Using Memory-Efficient Context Trees

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2009, IEEE Transactions on Information Theory.

Protein Family Classification Using Sparse Markov Transducers

Eleazar Eskin, William Noble Grundy, Yoram Singer, 2000, ISMB.

Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy

Yoram Singer, Manfred K. Warmuth, Y. Singer, 1998, NIPS.

Boosting Applied to Tagging and PP Attachment

Yoram Singer, Robert E. Schapire, Steven Abney, 1999, EMNLP.

Phoneme Alignment using Large Margin Techniques

Y. Singer, Joseph Keshet, S. Shalev-Shwartz, 2005 .

L G ] 2 M ar 2 01 8 Shampoo : Preconditioned Stochastic Tensor Optimization

Y. Singer, Tomer Koren, Vineet Gupta, 2018 .

Proximal and First-Order Methods for Convex Optimization

Yoram Singer, John C. Duchi, Y. Singer, 2013 .

A Coordinate Descent Algorithm for Learning Compact Ranking Functions

Y. Singer, Samy Bengio, Mark Stevens, 2010 .

Are All Layers Created Equal? pdf

Samy Bengio, Yoram Singer, Chiyuan Zhang, 2019, J. Mach. Learn. Res..

SIGIR ’ 98 Boosting and Rocchio Applied to Text Filtering

R. Schapire, Y. Singer, F. Park, 2015 .

Smooth epsiloon-Insensitive Regression by Loss Symmetrization

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2005, Journal of machine learning research.

Multiclass Categorization by Probabilistic Embeddings

Yoram Singer, Ofer Dekel, Y. Singer, 2003 .

Error Correcting Output Codes

Yoram Singer, Rob Schapire, Erin Allwein, 2010, Encyclopedia of Machine Learning.

Towards learning a metric for neural prosthetics

Yoram Singer, Jonathon Shlens, Nishal P. Shah, 2018 .

Adaptive Mixture of Probabilistic Transducers

Yoram Singer, Y. Singer, 1995, NIPS.

Guest Editor's Introduction

Yoram Singer, Y. Singer, 2004, Machine Learning.

Full Matrix Preconditioning Made Practical

Yoram Singer, Tomer Koren, Kevin Regan, 2019 .

Inferring probabilistic acyclic automata using the minimum description length principle

Naftali Tishby, Y. Singer, Y. Singer, 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

Context-sensitive learning methods for text categorization

William W. Cohen, Y. Singer, 1999, TOIS.

A comparison of new and old algorithms for a mixture estimation problem

Manfred K. Warmuth, R. Schapire, Y. Singer, 1995, COLT '95.

Response model

Y. Singer, Jonathon Shlens, C. Fernandez-Granda, 2015 .

Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces

Yoram Singer, Eilon Vaadia, Rony Paz, 2005, Neural Computation.

Special Issue on Data Mining in Finance C World Scientific Publishing Company Switching Portfolios

Y. Singer, Switching Portfolios, 2010 .

A Markovian Lattice Model for the Acquisition of Morphological Structure

Y. Singer, D. Ron, L. Kontorovich, 2003 .

On the learnability and usage of acyclic probabilistic finite automata

Dana Ron, Yoram Singer, Naftali Tishby, 1995, COLT '95.

An Efficient Extension to Mixture Techniques for Prediction and Decision Trees

Y. Singer, Fernando C Pereira, 1997, COLT.

The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length

Y. Singer, D. Ron, Naftali Tishby, 2005, Machine-mediated learning.

Parallel Boosting with Momentum

Yoram Singer, Kevin Robert Canini, Rafael M. Frongillo, 2013, ECML/PKDD.

Protein Family Classification Using Sparse Markov Transducers

Eleazar Eskin, Yoram Singer, William Stafford Noble, 2000, J. Comput. Biol..

Using Substitution Matrices to Estimate Probability Distributions for Biological Sequences

Eleazar Eskin, Yoram Singer, William Stafford Noble, 2002, J. Comput. Biol..

Short and Deep: Sketching and Neural Networks

Yoram Singer, Nevena Lazic, Amit Daniely, 2017, ICLR.

Sketching and Neural Networks pdf

Yoram Singer, Nevena Lazic, Amit Daniely, 2016, ArXiv.

"What has been will be again": a machine learning approach to the analysis of natural language

Y. Singer, Yoram Singer, Naftali Tishby, 1995 .

Leveraging the margin more carefully

Yoram Singer, Nir Krause, Y. Singer, 2004, ICML.

A Simple, Fast, and Effictive Rule Learner

William W. Cohen, Y. Singer, 1999, AAAI/IAAI.

Unsupervised Models for Named Entity Classification

Yoram Singer, Michael Collins, Y. Singer, 1999, EMNLP.

BoosTexter: A System for Multiclass Multi-label Text Categorization

Yoram Singer, Robert E. Schapire, R. Schapire, 1998 .

Memory Efficient Adaptive Optimization

Yoram Singer, Vineet Gupta, Rohan Anil, 2019, NeurIPS.

Shampoo: Preconditioned Stochastic Tensor Optimization

Yoram Singer, Vineet Gupta, Tomer Koren, 2018, ICML.

Robust temporal and spectral modeling for query By melody

Shlomo Dubnov, Yoram Singer, Shai Shalev-Shwartz, 2002, SIGIR '02.

A New Parameter Estimation Method for Gaussian Mixtures

Yoram Singer, Manfred K. Warmuth, Y. Singer, 1998, NIPS 1998.

Identity Crisis: Memorization and Generalization under Extreme Overparameterization pdf

Samy Bengio, Yoram Singer, Moritz Hardt, 2019, ICLR.

Entire Relaxation Path for Maximum Entropy Problems

Yoram Singer, Moshe Dubiner, Y. Singer, 2011, EMNLP.

Decoding Cursive Scripts

Yoram Singer, Naftali Tishby, Y. Singer, 1993, NIPS.

The Maximum Entropy Relaxation Path pdf

Yoram Singer, Moshe Dubiner, Matan Gavish, 2013, ArXiv.

Part-of-Speech Tagging Using a Variable Memory Markov Model

Hinrich Schütze, Yoram Singer, Y. Singer, 1994, ACL.

Online Learning of Multiple Tasks with a Shared Loss

Philip M. Long, Yoram Singer, Ofer Dekel, 2007, J. Mach. Learn. Res..

Leveraged Vector Machines

Yoram Singer, Y. Singer, 1999, NIPS.

Local Low-Rank Matrix Approximation

Yoram Singer, Guy Lebanon, Joonseok Lee, 2013, ICML.

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Yoram Singer, Amit Daniely, Roy Frostig, 2016, NIPS.

Support Vector Machines on a Budget

Yoram Singer, Ofer Dekel, Y. Singer, 2006, NIPS.

Discriminative kernel-based phoneme sequence recognition

Samy Bengio, Yoram Singer, Shai Shalev-Shwartz, 2006, INTERSPEECH.

The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees

Yoram Singer, Shai Shalev-Shwartz, Ofer Dekel, 2004, NIPS.

Convolutional Bipartite Attractor Networks pdf

Yoram Singer, Michael C. Mozer, Michael L. Iuzzolino, 2019, ArXiv.

An Efficient Extension to Mixture Techniques for Prediction and Decision Trees

Yoram Singer, Fernando Pereira, Y. Singer, 1997, COLT '97.

LLORMA: Local Low-Rank Matrix Approximation

Samy Bengio, Yoram Singer, Guy Lebanon, 2016, J. Mach. Learn. Res..

Online multiclass learning by interclass hypothesis sharing

Yoram Singer, Shai Shalev-Shwartz, Shimon Ullman, 2006, ICML.

Memory-Efficient Adaptive Optimization for Large-Scale Learning pdf

Yoram Singer, Vineet Gupta, Rohan Anil, 2019, ArXiv.

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

John C. Duchi, Elad Hazan, Y. Singer, 2011 .

Second Order Optimization Made Practical pdf

Yoram Singer, Vineet Gupta, Rohan Anil, 2020, ArXiv.

A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization pdf

Yoram Singer, Vineet Gupta, Tomer Koren, 2017, ArXiv.

Random Features for Compositional Kernels pdf

Yoram Singer, Amit Daniely, Vineet Gupta, 2017, ArXiv.

Dynamical encoding of cursive handwriting

Yoram Singer, Naftali Tishby, Y. Singer, 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

Âóùöòòð Óó Öøø¬ Blockin

William W. Cohen, R. Schapire, Y. Singer, 2007 .

A simple, fast, and effective rule learner

Yoram Singer, William W. Cohen, Y. Singer, 1999, AAAI 1999.

A Markov model for the acquisition of morphological structure

Dana Ron, Yoram Singer, Leonid Kontorovich, 2003 .

An Efficient PAC Algorithm for Reconstructing a Mixture of Lines

Sanjoy Dasgupta, Yoram Singer, Elan Pavlov, 2002, ALT.

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

John C. Duchi, Elad Hazan, Y. Singer, 2011 .

Pegasos: Primal Estimated sub-GrAdient SOlver for SVM

Y. Singer, S. Shalev-Shwartz, Andrew Cotter, 2011, ICML.

Online Learning of Complex Prediction Problems Using Simultaneous Projections

Yoram Singer, Shai Shalev-Shwartz, Yonatan Amit, 2008, J. Mach. Learn. Res..

Online Classification on a Budget

Koby Crammer, Yoram Singer, Jaz S. Kandola, 2003, NIPS.

Phoneme alignment based on discriminative learning

Yoram Singer, Shai Shalev-Shwartz, Joseph Keshet, 2005, INTERSPEECH.

Loss Bounds for Online Category Ranking

Koby Crammer, Yoram Singer, Y. Singer, 2005, COLT.

Efficient Learning of Sparse Ranking Functions

Samy Bengio, Yoram Singer, Mark Stevens, 2013, Empirical Inference.

Learning to Order Things

William W. Cohen, R. Schapire, Y. Singer, 2011, NIPS.

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

John C. Duchi, Elad Hazan, Y. Singer, 2011, J. Mach. Learn. Res..

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Y. Singer, Roy Frostig, Amit Daniely, 2016, NIPS.

Individual variability of neural computations in the primate retina

Nishal P. Shah, Y. Singer, Jonathon Shlens, 2021, Neuron.

Pegasos: primal estimated sub-gradient solver for SVM

Y. Singer, S. Shalev-Shwartz, Andrew Cotter, 2007, ICML '07.

Data-Driven Online to Batch Conversions

Yoram Singer, Ofer Dekel, Y. Singer, 2005, NIPS.

Finding a path is harder than finding a tree

William W. Cohen, R. Schapire, Y. Singer, 2001, AISTATS.

Âóùöòòð Óó Öøø¬ Blockin

William W. Cohen, R. Schapire, Y. Singer, 2022 .

Online Multitask Learning

Philip M. Long, Yoram Singer, Ofer Dekel, 2006, COLT.

Efficient Learning of Label Ranking by Soft Projections onto Polyhedra

Yoram Singer, Shai Shalev-Shwartz, Y. Singer, 2006, J. Mach. Learn. Res..

The Well Tempered Lasso

Yuanzhi Li, Yoram Singer, Y. Singer, 2018, ICML.

Spikernels: Embedding Spiking Neurons in Inner-Product Spaces

Yoram Singer, Eilon Vaadia, Rony Paz, 2002, NIPS.

Using Web Co-occurrence Statistics for Improving Image Categorization pdf

Samy Bengio, Dumitru Erhan, Quoc V. Le, 2013, ArXiv.

A Large Margin Algorithm for Speech-to-Phoneme and Music-to-Score Alignment

Yoram Singer, Shai Shalev-Shwartz, Joseph Keshet, 2007, IEEE Transactions on Audio, Speech, and Language Processing.

An Efficient Boosting Algorithm for Combining Preferences

Y. Freund, R. Schapire, Y. Singer, 1998, J. Mach. Learn. Res..

Âóùöòòð Óó Öøø¬ Blockin

William W. Cohen, R. Schapire, Y. Singer, 2022 .