Yoram Singer, Ph.D - Publications

Affiliations: 
Google research, Hebrew University 
Area:
Machine Learning

94 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2014 Lee J, Bengio S, Kim S, Lebanon G, Singer Y. Local collaborative ranking Www 2014 - Proceedings of the 23rd International Conference On World Wide Web. 85-95. DOI: 10.1145/2566486.2567970  1
2013 Stevens M, Bengio S, Singer Y. Efficient learning of sparse ranking functions Empirical Inference: Festschrift in Honor of Vladimir N. Vapnik. 261-271. DOI: 10.1007/978-3-642-41136-6_22  1
2013 Mukherjee I, Canini K, Frongillo R, Singer Y. Parallel boosting with momentum Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8190: 17-32. DOI: 10.1007/978-3-642-40994-3_2  1
2013 Lee J, Kim S, Lebanon G, Singer Y. Local low-rank matrix approximation 30th International Conference On Machine Learning, Icml 2013. 741-749.  1
2011 Shalev-Shwartz S, Singer Y, Srebro N, Cotter A. Pegasos: Primal estimated sub-gradient solver for SVM Mathematical Programming. 127: 3-30. DOI: 10.1007/s10107-010-0420-4  1
2011 Dubiner M, Singer Y. Entire relaxation path for maximum entropy problems Emnlp 2011 - Conference On Empirical Methods in Natural Language Processing, Proceedings of the Conference. 941-948.  1
2011 Duchi J, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization Journal of Machine Learning Research. 12: 2121-2159.  1
2010 Shalev-Shwartz S, Singer Y. On the equivalence of weak learnability and linear separability: New relaxations and efficient boosting algorithms Machine Learning. 80: 141-163. DOI: 10.1007/s10994-010-5173-z  1
2010 Duchi JC, Shalev-Shwartz S, Singer Y, Tewari A. Composite objective mirror descent Colt 2010 - the 23rd Conference On Learning Theory. 14-26.  1
2009 Duchi J, Singer Y. Boosting with structural sparsity Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 297-304. DOI: 10.1145/1553374.1553412  1
2009 Dekel O, Shalev-Shwartz S, Singer Y. Individual sequence prediction using memory-efficient context trees Ieee Transactions On Information Theory. 55: 5251-5262. DOI: 10.1109/TIT.2009.2030460  1
2009 Keshet J, Shalev-Shwartz S, Singer Y, Chazan D. A Large Margin Algorithm for Forced Alignment Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods. 51-68. DOI: 10.1002/9780470742044.ch4  1
2009 Duchi J, Singer Y. Efficient online and batch learning using forward backward splitting Journal of Machine Learning Research. 10: 2899-2934.  1
2009 Bengio S, Pereira F, Singer Y, Strelow D. Group sparse coding Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 82-89.  1
2009 Duchi J, Singer Y. Efficient learning using forward-backward splitting Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 495-503.  1
2008 Duchi J, Shalev-Shwartz S, Singer Y, Chandra T. Efficient projections onto the ℓ1-ball for learning in high dimensions Proceedings of the 25th International Conference On Machine Learning. 272-279.  1
2008 Amit Y, Shalev-Shwartz S, Singer Y. Online learning of complex prediction problems using simultaneous projections Journal of Machine Learning Research. 9: 1399-1435.  1
2007 Dekel O, Shai SS, Singer Y. The forgetron: A kernel-based perceptron on a budget Siam Journal On Computing. 37: 1342-1372. DOI: 10.1137/060666998  1
2007 Keshet J, Shalev-Shwartz S, Singer Y, Chazan D. A large margin algorithm for speech-to-phoneme and music-to-score alignment Ieee Transactions On Audio, Speech and Language Processing. 15: 2373-2382. DOI: 10.1109/TASL.2007.903928  1
2007 Frome A, Sha F, Singer Y, Malik J. Learning globally-consistent local distance functions for shape-based image retrieval and classification Proceedings of the Ieee International Conference On Computer Vision. DOI: 10.1109/ICCV.2007.4408839  1
2007 Shalev-Shwartz S, Singer Y. A primal-dual perspective of online learning algorithms Machine Learning. 69: 115-142. DOI: 10.1007/s10994-007-5014-x  1
2007 Shalev-Shwartz S, Singer Y. Convex repeated games and Fenchel duality Advances in Neural Information Processing Systems. 1265-1272.  1
2007 Amit Y, Shalev-Shwartz S, Singer Y. Online classification for complex problems using simultaneous projections Advances in Neural Information Processing Systems. 17-24.  1
2007 Amit Y, Dekel O, Singer Y. A boosting algorithm for label covering in multilabel problems Journal of Machine Learning Research. 2: 27-34.  1
2007 Frome A, Singer Y, Malik J. Image retrieval and classification using local distance functions Advances in Neural Information Processing Systems. 417-424.  1
2007 Shalev-Shwartz S, Singer Y. A unified algorithmic approach for efficient online label ranking Journal of Machine Learning Research. 2: 452-459.  1
2007 Dekel O, Singer Y. Support Vector Machines on a budget Advances in Neural Information Processing Systems. 345-352.  1
2007 Dekel O, Long PM, Singer Y. Online learning of multiple tasks with a shared loss Journal of Machine Learning Research. 8: 2233-2264.  1
2006 Fink M, Shalev-Shwartz S, Singer Y, Ullman S. Online multiclass learning by interclass hypothesis sharing Acm International Conference Proceeding Series. 148: 313-320. DOI: 10.1145/1143844.1143884  1
2006 Keshet J, Shalev-Shwartz S, Bengio S, Singer Y, Chazan D. Discriminative Kernel-based phoneme sequence recognition Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech. 2: 593-596.  1
2006 Shaley-Shwartz S, Singer Y. Efficient learning of label ranking by soft projections onto polyhedra Journal of Machine Learning Research. 7: 1567-1599.  1
2006 Crammer K, Dekel O, Keshet J, Shalev-Shwartz S, Singer Y. Online passive-aggressive algorithms Journal of Machine Learning Research. 7: 551-585.  1
2006 Dekel O, Long PM, Singer Y. Online multitask learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4005: 453-467.  1
2006 Shalev-Shwartz S, Singer Y. Online learning meets optimization in the dual Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4005: 423-437.  1
2005 Shpigelman L, Singer Y, Paz R, Vaadia E. Spikernels: predicting arm movements by embedding population spike rate patterns in inner-product spaces. Neural Computation. 17: 671-90. PMID 15802010 DOI: 10.1162/0899766053019944  1
2005 Crammer K, Singer Y. Online ranking by projecting. Neural Computation. 17: 145-75. PMID 15563751 DOI: 10.1162/0899766052530848  0.68
2005 Crammer K, Singer Y. Loss bounds for online category ranking Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3559: 48-62.  1
2005 Dekel O, Singer Y. Data-driven online to batch conversions Advances in Neural Information Processing Systems. 267-274.  1
2005 Dekel O, Shalev-Shwartz S, Singer Y. The Forgetron: A kernel-based Perceptron on a fixed budget Advances in Neural Information Processing Systems. 259-266.  1
2005 Shalev-Shwartz S, Singer Y. A new perspective on an old perceptron algorithm Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3559: 264-278.  1
2005 Keshet J, Shalev-Shwartz S, Singer Y, Chazan D. Phoneme alignment based on discriminative learning 9th European Conference On Speech Communication and Technology. 2961-2964.  1
2005 Dekel O, Keshet J, Singer Y. An online algorithm for hierarchical phoneme classification Lecture Notes in Computer Science. 3361: 146-158.  0.36
2005 Dekel O, Shalev-Shwartz S, Singer Y. Smooth ε-insensitive regression by loss symmetrization Journal of Machine Learning Research. 6.  1
2005 Shpigelman L, Crammer K, Paz R, Vaadia E, Singer Y. A temporal kernel-based model for tracking hand-movements from neural activities Advances in Neural Information Processing Systems 1
2005 Dekel O, Shalev-Shwartz S, Singer Y. The power of selective memory: Self-bounded learning of prediction suffix trees Advances in Neural Information Processing Systems 1
2004 Freund Y, Iyer R, Schapire RE, Singer Y. An efficient boosting algorithm for combining preferences Journal of Machine Learning Research. 4: 933-969. DOI: 10.1162/1532443041827916  1
2004 Shalev-Shwartz S, Singer Y, Ng AY. Online and batch learning of pseudo-metrics Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 743-750.  1
2004 Dekel O, Keshet J, Singer Y. Large margin hierarchical classification Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 209-216.  0.36
2004 Krause N, Singer Y. Leveraging the margin more carefully Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 496-503.  1
2004 Dekel O, Manning CD, Singer Y. Log-linear models for label ranking Advances in Neural Information Processing Systems 1
2004 Crammer K, Kandola J, Singer Y. Online classification on a budget Advances in Neural Information Processing Systems 1
2003 Eskin E, Noble WS, Singer Y. Protein family classification using sparse markov transducers. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 10: 187-213. PMID 12804091 DOI: 10.1089/106652703321825964  1
2003 Crammer K, Singer Y. A Family of Additive Online Algorithms for Category Ranking Journal of Machine Learning Research. 3: 1025-1058. DOI: 10.1162/153244303322533188  1
2003 Crammer K, Singer Y. Learning algorithms for enclosing points in bregmanian spheres Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2777: 388-402.  1
2003 Crammer K, Singer Y. Ultraconservative online algorithms for multiclass problems Journal of Machine Learning Research. 3: 951-991.  1
2003 Dekel O, Singer Y. Multiclass learning by probabilistic embeddings Advances in Neural Information Processing Systems 1
2003 Crammer K, Keshet J, Singer Y. Kernel design using boosting Advances in Neural Information Processing Systems 1
2003 Ben-Reuven E, Singer Y. Discriminative binaural sound localization Advances in Neural Information Processing Systems 1
2003 Shpigelman L, Singer Y, Paz R, Vaadia E. Spikerneis: Embedding spiking neurons in inner-product spaces Advances in Neural Information Processing Systems 1
2002 Eskin E, Noble WS, Singer Y. Using substitution matrices to estimate probability distributions for biological sequences. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 9: 775-91. PMID 12614546 DOI: 10.1089/10665270260518263  1
2002 Collins M, Schapire RE, Singer Y. Logistic regression, AdaBoost and Bregman distances Machine Learning. 48: 253-285. DOI: 10.1023/A:1013912006537  1
2002 Crammer K, Singer Y. On the learnability and design of output codes for multiclass problems Machine Learning. 47: 201-233. DOI: 10.1023/A:1013637720281  1
2002 Shalev-Shwartz S, Dubnov S, Friedman N, Singer Y. Robust temporal and spectral modeling for query by melody Sigir Forum (Acm Special Interest Group On Information Retrieval). 331-338.  1
2002 Crammer K, Singer Y. A new family of online algorithms for category ranking Sigir Forum (Acm Special Interest Group On Information Retrieval). 151-158.  1
2002 Dasgupta S, Pavlov E, Singer Y. An efficient PAC algorithm for reconstructing a mixture of lines Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2533: 351-364.  1
2002 Crammer K, Singer Y. Pranking with ranking Advances in Neural Information Processing Systems 1
2001 Eskin E, Grundy WN, Singer Y. Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences. Bioinformatics (Oxford, England). 17: S65-73. PMID 11472994  1
2001 Singer Y. Guest editor's introduction Machine Learning. 43: 171-172. DOI: 10.1023/A:1010875511248  1
2001 Anker T, Cohen R, Dolev D, Singer Y. Probabilistic fair queuing 2001 Ieee Workshop On High Performance Switching and Routing. 397-401.  1
2001 Allwein EL, Schapire RE, Singer Y. Reducing multiclass to binary: A unifying approach for margin classifiers Journal of Machine Learning Research. 1: 113-141.  1
2001 Crammer K, Singer Y. Improved output coding for classification using continuous relaxation Advances in Neural Information Processing Systems 1
2000 Eskin E, Grundy WN, Singer Y. Protein family classification using sparse Markov transducers. Proceedings / ... International Conference On Intelligent Systems For Molecular Biology ; Ismb. International Conference On Intelligent Systems For Molecular Biology. 8: 134-45. PMID 10977074  1
2000 Schapire RE, Singer Y. BoosTexter: a boosting-based system for text categorization Machine Learning. 39: 135-168.  1
2000 Singer Y. Leveraged vector machines Advances in Neural Information Processing Systems. 610-616.  1
1999 Pereira FC, Singer Y. Efficient extension to mixture techniques for prediction and decision trees Machine Learning. 36: 183-199. DOI: 10.1023/A:1007670818503  1
1999 Schapire RE, Singer Y. Improved boosting algorithms using confidence-rated predictions Machine Learning. 37: 297-336. DOI: 10.1023/A:1007614523901  1
1999 Cohen WW, Singer Y. Context-sensitive learning methods for text categorization Acm Transactions On Information Systems. 17: 141-173.  1
1999 Singer Y, Warmuth MK. Batch and on-line parameter estimation of Gaussian mixtures based on the joint entropy Advances in Neural Information Processing Systems. 578-584.  1
1999 Cohen WW, Schapire RE, Singer Y. Learning to order things Journal of Artificial Intelligence Research. 10: 243-270.  1
1999 Friedman N, Singer Y. Efficient Bayesian parameter estimation in large discrete domains Advances in Neural Information Processing Systems. 417-423.  1
1999 Cohen WW, Singer Y. Simple, fast, and effective rule learner Proceedings of the National Conference On Artificial Intelligence. 335-342.  1
1998 Fine S, Singer Y, Tishby N. Hierarchical Hidden Markov Model: Analysis and applications Machine Learning. 32: 41-62. DOI: 10.1023/A:1007469218079  1
1998 Helmbold DP, Schapire RE, Singer Y, Warmuth MK. On-line portfolio selection using multiplicative updates Mathematical Finance. 8: 325-347.  1
1998 Ron D, Singer Y, Tishby N. On the Learnability and Usage of Acyclic Probabilistic Finite Automata Journal of Computer and System Sciences. 56: 133-152.  1
1998 Schapire RE, Singer Y, Singhal A. Boosting and Rocchio applied to text filtering Sigir Forum (Acm Special Interest Group On Information Retrieval). 215-223.  1
1997 Singer Y. Switching portfolios. International Journal of Neural Systems. 8: 445-55. PMID 9730020  1
1997 Helmbold DP, Schapire RE, Singer Y, Warmuth MK. A Comparison of New and Old Algorithms for a Mixture Estimation Problem Machine Learning. 27: 97-119.  1
1997 Singer Y. Adaptive Mixtures of Probabilistic Transducers Neural Computation. 9: 1711-1733.  1
1997 Singer Y, Warmuth MK. Training algorithms for hidden Markov models using entropy based distance functions Advances in Neural Information Processing Systems. 641-647.  1
1997 Freund Y, Schapire RE, Singer Y, Warmuth MK. Using and combining predictors that specialize Conference Proceedings of the Annual Acm Symposium On Theory of Computing. 334-343.  1
1996 Ron D, Singer Y, Tishby N. The power of amnesia: Learning probabilistic automata with variable memory length Machine Learning. 25: 117-149.  1
1995 Berger P, Gruszka S, Gottlieb I, Singer Y. Performance of level 3 BLAS kernels in a dynamically partitioned data-flow environment Computing Systems in Engineering. 6: 357-361. DOI: 10.1016/0956-0521(95)00050-X  1
1994 Singer Y, Tishby N. Dynamical encoding of cursive handwriting. Biological Cybernetics. 71: 227-37. PMID 7918801 DOI: 10.1007/BF00202762  1
1994 Singer Y, Tishby N. Inferring probabilistic acyclic automata using the minimum description length principle Ieee International Symposium On Information Theory - Proceedings. 392. DOI: 10.1109/ISIT.1994.394627  1
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