Yoram Singer - RankMe

163 papers A* 46A 8B 2Journal 61Unranked 44

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Are All Layers Created Equal? J. Mach. Learn. Res. Chiyuan Zhang, Samy Bengio, Yoram Singer
2020	B	`conf`	Exponentiated Gradient Meets Gradient Descent. ALT Udaya Ghai, Elad Hazan, Yoram Singer
2020	A*	`conf`	Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. ICLR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer
2020	A*	`conf`	Proximity Preserving Binary Code Using Signed Graph-Cut. AAAI Inbal Lavi, Shai Avidan, Yoram Singer, Yacov Hel-Or
2020	J	`jnl`	Proximity Preserving Binary Code using Signed Graph-Cut. CoRR Inbal Lavi, Shai Avidan, Yoram Singer, Yacov Hel-Or
2020	J	`jnl`	Second Order Optimization Made Practical. CoRR Rohan Anil, Vineet Gupta, Tomer Koren, Kevin Regan, Yoram Singer
2019	J	`jnl`	Are All Layers Created Equal? CoRR Chiyuan Zhang, Samy Bengio, Yoram Singer
2019	J	`jnl`	Convolutional Bipartite Attractor Networks. CoRR Michael L. Iuzzolino, Yoram Singer, Michael C. Mozer
2019	J	`jnl`	Exponentiated Gradient Meets Gradient Descent. CoRR Udaya Ghai, Elad Hazan, Yoram Singer
2019	J	`jnl`	Identity Crisis: Memorization and Generalization under Extreme Overparameterization. CoRR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Yoram Singer
2019	A*	`conf`	Memory Efficient Adaptive Optimization. NeurIPS Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer
2019	J	`jnl`	Memory-Efficient Adaptive Optimization for Large-Scale Learning. CoRR Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer
2018	—	`conf`	Learning a neural response metric for retinal prosthesis. ICLR (Poster) Nishal P. Shah, Sasidhar Madugula, E. J. Chichilnisky, Yoram Singer, Jonathon Shlens
2018	A*	`conf`	Shampoo: Preconditioned Stochastic Tensor Optimization. ICML Vineet Gupta, Tomer Koren, Yoram Singer
2018	J	`jnl`	Shampoo: Preconditioned Stochastic Tensor Optimization. CoRR Vineet Gupta, Tomer Koren, Yoram Singer
2018	J	`jnl`	The Well Tempered Lasso. CoRR Yuanzhi Li, Yoram Singer
2018	A*	`conf`	The Well-Tempered Lasso. ICML Yuanzhi Li, Yoram Singer
2017	J	`jnl`	A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization. CoRR Vineet Gupta, Tomer Koren, Yoram Singer
2017	J	`jnl`	Random Features for Compositional Kernels. CoRR Amit Daniely, Roy Frostig, Vineet Gupta, Yoram Singer
2017	—	`conf`	Short and Deep: Sketching and Neural Networks. ICLR (Workshop) Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar
2016	J	`jnl`	A Stochastic Quasi-Newton Method for Large-Scale Optimization. SIAM J. Optim. Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer
2016	J	`jnl`	LLORMA: Local Low-Rank Matrix Approximation. J. Mach. Learn. Res. Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer, Samy Bengio
2016	J	`jnl`	Sketching and Neural Networks. CoRR Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar
2016	—	`conf`	Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. NIPS Amit Daniely, Roy Frostig, Yoram Singer
2016	J	`jnl`	Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. CoRR Amit Daniely, Roy Frostig, Yoram Singer
2016	A*	`conf`	Train faster, generalize better: Stability of stochastic gradient descent. ICML Moritz Hardt, Ben Recht, Yoram Singer
2015	J	`jnl`	Train faster, generalize better: Stability of stochastic gradient descent. CoRR Moritz Hardt, Benjamin Recht, Yoram Singer
2014	J	`jnl`	A Stochastic Quasi-Newton Method for Large-Scale Optimization. CoRR Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer
2014	A*	`conf`	Local collaborative ranking. WWW Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon, Yoram Singer
2014	—	`conf`	Zero-Shot Learning by Convex Combination of Semantic Embeddings. ICLR Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean
2013	—	`conf`	Efficient Learning of Sparse Ranking Functions. Empirical Inference Mark Stevens, Samy Bengio, Yoram Singer
2013	—	`conf`	Local Low-Rank Matrix Approximation. ICML (2) Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer
2013	—	`conf`	Matrix Approximation under Local Low-Rank Assumption ICLR (Workshop Poster) Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer
2013	—	`conf`	Parallel Boosting with Momentum. ECML/PKDD (3) Indraneel Mukherjee, Kevin Robert Canini, Rafael M. Frongillo, Yoram Singer
2013	J	`jnl`	Switching Portfolios CoRR Yoram Singer
2013	J	`jnl`	The Maximum Entropy Relaxation Path. CoRR Moshe Dubiner, Matan Gavish, Yoram Singer
2013	J	`jnl`	Update Rules for Parameter Estimation in Bayesian Networks CoRR Eric Bauer, Daphne Koller, Yoram Singer
2013	J	`jnl`	Using Web Co-occurrence Statistics for Improving Image Categorization. CoRR Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer
2011	J	`jnl`	Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. J. Mach. Learn. Res. John C. Duchi, Elad Hazan, Yoram Singer
2011	A*	`conf`	Entire Relaxation Path for Maximum Entropy Problems. EMNLP Moshe Dubiner, Yoram Singer
2011	J	`jnl`	Learning to Order Things CoRR William W. Cohen, Robert E. Schapire, Yoram Singer
2011	J	`jnl`	Pegasos: primal estimated sub-gradient solver for SVM. Math. Program. Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter
2010	A*	`conf`	Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. COLT John C. Duchi, Elad Hazan, Yoram Singer
2010	A*	`conf`	Composite Objective Mirror Descent. COLT John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari
2010	J	`jnl`	On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms. Mach. Learn. Shai Shalev-Shwartz, Yoram Singer
2009	A*	`conf`	Boosting with structural sparsity. ICML John C. Duchi, Yoram Singer
2009	—	`conf`	Efficient Learning using Forward-Backward Splitting. NIPS John C. Duchi, Yoram Singer
2009	J	`jnl`	Efficient Online and Batch Learning Using Forward Backward Splitting. J. Mach. Learn. Res. John C. Duchi, Yoram Singer
2009	—	`conf`	Group Sparse Coding. NIPS Samy Bengio, Fernando C. N. Pereira, Yoram Singer, Dennis Strelow
2009	J	`jnl`	Individual sequence prediction using memory-efficient context trees. IEEE Trans. Inf. Theory Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2008	—	`ed.`	Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 3-6, 2007 NIPS John C. Platt, Daphne Koller, Yoram Singer, Sam T. Roweis
2008	A*	`conf`	Efficient projections onto the ICML John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra
2008	A*	`conf`	On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms. COLT Shai Shalev-Shwartz, Yoram Singer
2008	J	`jnl`	Online Learning of Complex Prediction Problems Using Simultaneous Projections. J. Mach. Learn. Res. Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer
2008	J	`jnl`	The Forgetron: A Kernel-Based Perceptron on a Budget. SIAM J. Comput. Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2007	A	`conf`	A Boosting Algorithm for Label Covering in Multilabel Problems. AISTATS Yonatan Amit, Ofer Dekel, Yoram Singer
2007	J	`jnl`	A Large Margin Algorithm for Speech-to-Phoneme and Music-to-Score Alignment. IEEE Trans. Speech Audio Process. Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Dan Chazan
2007	A	`conf`	A Unified Algorithmic Approach for Efficient Online Label Ranking. AISTATS Shai Shalev-Shwartz, Yoram Singer
2007	J	`jnl`	A primal-dual perspective of online learning algorithms. Mach. Learn. Shai Shalev-Shwartz, Yoram Singer
2007	A*	`conf`	Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. ICCV Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik
2007	J	`jnl`	Online Learning of Multiple Tasks with a Shared Loss. J. Mach. Learn. Res. Ofer Dekel, Philip M. Long, Yoram Singer
2007	A*	`conf`	Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. ICML Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
2006	—	`conf`	Convex Repeated Games and Fenchel Duality. NIPS Shai Shalev-Shwartz, Yoram Singer
2006	A	`conf`	Discriminative kernel-based phoneme sequence recognition. INTERSPEECH Joseph Keshet, Shai Shalev-Shwartz, Samy Bengio, Yoram Singer, Dan Chazan
2006	J	`jnl`	Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. J. Mach. Learn. Res. Shai Shalev-Shwartz, Yoram Singer
2006	—	`conf`	Image Retrieval and Classification Using Local Distance Functions. NIPS Andrea Frome, Yoram Singer, Jitendra Malik
2006	—	`conf`	Online Classification for Complex Problems Using Simultaneous Projections. NIPS Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer
2006	A*	`conf`	Online Learning Meets Optimization in the Dual. COLT Shai Shalev-Shwartz, Yoram Singer
2006	A*	`conf`	Online Multitask Learning. COLT Ofer Dekel, Philip M. Long, Yoram Singer
2006	J	`jnl`	Online Passive-Aggressive Algorithms. J. Mach. Learn. Res. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer
2006	A*	`conf`	Online multiclass learning by interclass hypothesis sharing. ICML Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman
2006	—	`conf`	Support Vector Machines on a Budget. NIPS Ofer Dekel, Yoram Singer
2005	A*	`conf`	A New Perspective on an Old Perceptron Algorithm. COLT Shai Shalev-Shwartz, Yoram Singer
2005	—	`conf`	Data-Driven Online to Batch Conversions. NIPS Ofer Dekel, Yoram Singer
2005	A*	`conf`	Loss Bounds for Online Category Ranking. COLT Koby Crammer, Yoram Singer
2005	J	`jnl`	Online Ranking by Projecting. Neural Comput. Koby Crammer, Yoram Singer
2005	A	`conf`	Phoneme alignment based on discriminative learning. INTERSPEECH Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Dan Chazan
2005	J	`jnl`	Smooth epsiloon-Insensitive Regression by Loss Symmetrization. J. Mach. Learn. Res. Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2005	J	`jnl`	Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces. Neural Comput. Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia
2005	—	`conf`	The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. NIPS Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2004	—	`conf`	A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer
2004	—	`conf`	An Online Algorithm for Hierarchical Phoneme Classification. MLMI Ofer Dekel, Joseph Keshet, Yoram Singer
2004	A*	`conf`	Large margin hierarchical classification. ICML Ofer Dekel, Joseph Keshet, Yoram Singer
2004	A*	`ed.`	Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings COLT John Shawe-Taylor, Yoram Singer
2004	—	`conf`	Learning to Align Polyphonic Music. ISMIR Shai Shalev-Shwartz, Joseph Keshet, Yoram Singer
2004	A*	`conf`	Leveraging the margin more carefully. ICML Nir Krause, Yoram Singer
2004	A*	`conf`	Online and batch learning of pseudo-metrics. ICML Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
2004	—	`conf`	The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. NIPS Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2003	J	`jnl`	A Family of Additive Online Algorithms for Category Ranking. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2003	J	`jnl`	An Efficient Boosting Algorithm for Combining Preferences. J. Mach. Learn. Res. Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer
2003	—	`conf`	Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. HLT-NAACL Kristina Toutanova, Dan Klein, Christopher D. Manning, Yoram Singer
2003	A*	`conf`	Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT Koby Crammer, Yoram Singer
2003	—	`conf`	Log-Linear Models for Label Ranking. NIPS Ofer Dekel, Christopher D. Manning, Yoram Singer
2003	—	`conf`	Online Classification on a Budget. NIPS Koby Crammer, Jaz S. Kandola, Yoram Singer
2003	—	`conf`	Online Passive-Aggressive Algorithms. NIPS Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer
2003	J	`jnl`	Protein Family Classification Using Sparse Markov Transducers. J. Comput. Biol. Eleazar Eskin, William Stafford Noble, Yoram Singer
2003	A*	`conf`	Smooth e-Intensive Regression by Loss Symmetrization. COLT Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
2003	J	`jnl`	Ultraconservative Online Algorithms for Multiclass Problems. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2002	A*	`conf`	A new family of online algorithms for category ranking. SIGIR Koby Crammer, Yoram Singer
2002	B	`conf`	An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. ALT Sanjoy Dasgupta, Elan Pavlov, Yoram Singer
2002	—	`conf`	Discriminative Binaural Sound Localization. NIPS Ehud Ben-Reuven, Yoram Singer
2002	—	`conf`	Kernel Design Using Boosting. NIPS Koby Crammer, Joseph Keshet, Yoram Singer
2002	J	`jnl`	Logistic Regression, AdaBoost and Bregman Distances. Mach. Learn. Michael Collins, Robert E. Schapire, Yoram Singer
2002	—	`conf`	Multiclass Learning by Probabilistic Embeddings. NIPS Ofer Dekel, Yoram Singer
2002	J	`jnl`	On the Learnability and Design of Output Codes for Multiclass Problems. Mach. Learn. Koby Crammer, Yoram Singer
2002	A*	`conf`	Robust temporal and spectral modeling for query By melody. SIGIR Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer
2002	—	`conf`	Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. NIPS Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia
2002	J	`jnl`	Using Substitution Matrices to Estimate Probability Distributions for Biological Sequences. J. Comput. Biol. Eleazar Eskin, William Stafford Noble, Yoram Singer
2001	J	`jnl`	Guest Editor's Introduction. Mach. Learn. Yoram Singer
2001	J	`jnl`	On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2001	—	`conf`	Pranking with Ranking. NIPS Koby Crammer, Yoram Singer
2001	—	`conf`	Ultraconservative Online Algorithms for Multiclass Problems. COLT/EuroCOLT Koby Crammer, Yoram Singer
2001	—	`conf`	Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences. ISMB (Supplement of Bioinformatics) Eleazar Eskin, William Noble Grundy, Yoram Singer
2000	J	`jnl`	BoosTexter: A Boosting-based System for Text Categorization. Mach. Learn. Robert E. Schapire, Yoram Singer
2000	A	`conf`	Boosting for Document Routing. CIKM Raj D. Iyer, David D. Lewis, Robert E. Schapire, Yoram Singer, Amit Singhal
2000	—	`conf`	Improved Output Coding for Classification Using Continuous Relaxation. NIPS Koby Crammer, Yoram Singer
2000	A*	`conf`	Logistic Regression, AdaBoost and Bregman Distances. COLT Michael Collins, Robert E. Schapire, Yoram Singer
2000	A*	`conf`	On the Learnability and Design of Output Codes for Multiclass Problems. COLT Koby Crammer, Yoram Singer
2000	A	`conf`	Protein Family Classification Using Sparse Markov Transducers. ISMB Eleazar Eskin, William Noble Grundy, Yoram Singer
2000	A*	`conf`	Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. ICML Erin L. Allwein, Robert E. Schapire, Yoram Singer
2000	J	`jnl`	Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. J. Mach. Learn. Res. Erin L. Allwein, Robert E. Schapire, Yoram Singer
2000	A*	`conf`	State-based Classification of Finger Gestures from Electromyographic Signals. ICML Peter Ju, Leslie Pack Kaelbling, Yoram Singer
1999	—	`conf`	A Simple, Fast, and Effictive Rule Learner. AAAI/IAAI William W. Cohen, Yoram Singer
1999	J	`jnl`	An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. Mach. Learn. Fernando C. N. Pereira, Yoram Singer
1999	A*	`conf`	Boosting Applied to Tagging and PP Attachment. EMNLP Steven Abney, Robert E. Schapire, Yoram Singer
1999	J	`jnl`	Context-Sensitive Learning Methods for Text Categorization. ACM Trans. Inf. Syst. William W. Cohen, Yoram Singer
1999	J	`jnl`	Improved Boosting Algorithms Using Confidence-rated Predictions. Mach. Learn. Robert E. Schapire, Yoram Singer
1999	J	`jnl`	Learning to Order Things. J. Artif. Intell. Res. William W. Cohen, Robert E. Schapire, Yoram Singer
1999	—	`conf`	Leveraged Vector Machines. NIPS Yoram Singer
1999	A*	`conf`	Unsupervised Models for Named Entity Classification. EMNLP Michael Collins, Yoram Singer
1998	A*	`conf`	An Efficient Boosting Algorithm for Combining Preferences. ICML Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer
1998	—	`conf`	Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy. NIPS Yoram Singer, Manfred K. Warmuth
1998	A*	`conf`	Boosting and Rocchio Applied to Text Filtering. SIGIR Robert E. Schapire, Yoram Singer, Amit Singhal
1998	—	`conf`	Efficient Bayesian Parameter Estimation in Large Discrete Domains. NIPS Nir Friedman, Yoram Singer
1998	A*	`conf`	Improved Boosting Algorithms using Confidence-Rated Predictions. COLT Robert E. Schapire, Yoram Singer
1998	J	`jnl`	On the Learnability and Usage of Acyclic Probabilistic Finite Automata. J. Comput. Syst. Sci. Dana Ron, Yoram Singer, Naftali Tishby
1998	A	`conf`	Switching Portfolios. UAI Yoram Singer
1998	J	`jnl`	The Hierarchical Hidden Markov Model: Analysis and Applications. Mach. Learn. Shai Fine, Yoram Singer, Naftali Tishby
1997	J	`jnl`	A Comparison of New and Old Algorithms for a Mixture Estimation Problem. Mach. Learn. David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1997	J	`jnl`	Adaptive Mixtures of Probabilistic Transducers. Neural Comput. Yoram Singer
1997	A*	`conf`	An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. COLT Fernando C. N. Pereira, Yoram Singer
1997	—	`conf`	Learning to Order Things. NIPS William W. Cohen, Robert E. Schapire, Yoram Singer
1997	—	`conf`	Shared Context Probabilistic Transducers. NIPS Yoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer
1997	J	`jnl`	Switching Portfolios. Int. J. Neural Syst. Yoram Singer
1997	A	`conf`	Update Rules for Parameter Estimation in Bayesian Networks. UAI Eric Bauer, Daphne Koller, Yoram Singer
1997	A*	`conf`	Using and Combining Predictors That Specialize. STOC Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1996	J	`jnl`	Beyond Word N-Grams CoRR Fernando C. N. Pereira, Yoram Singer, Naftali Tishby
1996	A*	`conf`	Context-sensitive Learning Methods for Text Categorization. SIGIR William W. Cohen, Yoram Singer
1996	A*	`conf`	On-Line Portfolio Selection Using Multiplicative Updates. ICML David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1996	J	`jnl`	The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length. Mach. Learn. Dana Ron, Yoram Singer, Naftali Tishby
1996	—	`conf`	Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. NIPS Yoram Singer, Manfred K. Warmuth
1995	—	`—`	"What has been will be again": a machine learning approach to the analysis of natural language. Yoram Singer
1995	A*	`conf`	A Comparison of New and Old Algorithms for a Mixture Estimation Problem. COLT David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth
1995	—	`conf`	Adaptive Mixture of Probabilistic Transducers. NIPS Yoram Singer
1995	—	`conf`	Beyond Word N-Grams. VLC@ACL Fernando Pereira, Yoram Singer, Naftali Tishby
1995	A*	`conf`	On the Learnability and Usage of Acyclic Probabilistic Finite Automata. COLT Dana Ron, Yoram Singer, Naftali Tishby
1994	J	`jnl`	Dynamical encoding of cursive handwriting. Biol. Cybern. Yoram Singer, Naftali Tishby
1994	A*	`conf`	Learning Probabilistic Automata with Variable Memory Length. COLT Dana Ron, Yoram Singer, Naftali Tishby
1994	A*	`conf`	Part-of-Speech Tagging using a Variable Memory Markov Model. ACL Hinrich Schütze, Yoram Singer
1993	—	`conf`	Decoding Cursive Scripts. NIPS Yoram Singer, Naftali Tishby
1993	A*	`conf`	Dynamical encoding of cursive handwriting. CVPR Yoram Singer, Naftali Tishby
1993	—	`conf`	The Power of Amnesia. NIPS Dana Ron, Yoram Singer, Naftali Tishby
1992	—	`conf`	Learning class probabilities from labeled data. ICPR (2) Yoram Singer, Eyal Yair