| Adaptive subgradient methods for online learning and stochastic optimization J Duchi, E Hazan, Y Singer Journal of machine learning research 12 (Jul), 2121-2159, 2011 | 8166 | 2011 |
| Improved boosting algorithms using confidence-rated predictions RE Schapire, Y Singer Machine learning 37 (3), 297-336, 1999 | 4462 | 1999 |
| Feature-rich part-of-speech tagging with a cyclic dependency network K Toutanova, D Klein, CD Manning, Y Singer Proceedings of the 2003 conference of the North American chapter of the …, 2003 | 3837 | 2003 |
| BoosTexter: A boosting-based system for text categorization RE Schapire, Y Singer Machine learning 39 (2-3), 135-168, 2000 | 2884 | 2000 |
| On the algorithmic implementation of multiclass kernel-based vector machines K Crammer, Y Singer Journal of machine learning research 2 (Dec), 265-292, 2001 | 2614 | 2001 |
| An efficient boosting algorithm for combining preferences Y Freund, R Iyer, RE Schapire, Y Singer Journal of machine learning research 4 (Nov), 933-969, 2003 | 2578 | 2003 |
| Pegasos: Primal estimated sub-gradient solver for svm S Shalev-Shwartz, Y Singer, N Srebro, A Cotter Mathematical programming 127 (1), 3-30, 2011 | 2422 | 2011 |
| Reducing multiclass to binary: A unifying approach for margin classifiers EL Allwein, RE Schapire, Y Singer Journal of machine learning research 1 (Dec), 113-141, 2000 | 2377 | 2000 |
| Online passive-aggressive algorithms K Crammer, O Dekel, J Keshet, S Shalev-Shwartz, Y Singer Journal of Machine Learning Research 7 (Mar), 551-585, 2006 | 2082 | 2006 |
| Efficient projections onto the l1-ball for learning in high dimensions J Duchi, S Shalev-Shwartz, Y Singer, T Chandra Proceedings of the 25th international conference on Machine learning, 272-279, 2008 | 1305 | 2008 |
| The hierarchical hidden Markov model: Analysis and applications S Fine, Y Singer, N Tishby Machine learning 32 (1), 41-62, 1998 | 1239 | 1998 |
| Unsupervised models for named entity classification M Collins, Y Singer 1999 Joint SIGDAT Conference on Empirical Methods in Natural Language …, 1999 | 1198 | 1999 |
| On the learnability and design of output codes for multiclass problems K Crammer, Y Singer Machine learning 47 (2-3), 201-233, 2002 | 932 | 2002 |
| Context-sensitive learning methods for text categorization WW Cohen, Y Singer ACM Transactions on Information Systems (TOIS) 17 (2), 141-173, 1999 | 915 | 1999 |
| Learning to order things WW Cohen, RE Schapire, Y Singer Advances in neural information processing systems, 451-457, 1998 | 834 | 1998 |
| Logistic regression, AdaBoost and Bregman distances M Collins, RE Schapire, Y Singer Machine Learning 48 (1-3), 253-285, 2002 | 823 | 2002 |
| Pranking with ranking K Crammer, Y Singer Advances in neural information processing systems, 641-647, 2002 | 791 | 2002 |
| Ultraconservative online algorithms for multiclass problems K Crammer, Y Singer Journal of Machine Learning Research 3 (Jan), 951-991, 2003 | 703 | 2003 |
| The power of amnesia: Learning probabilistic automata with variable memory length D Ron, Y Singer, N Tishby Machine learning 25 (2-3), 117-149, 1996 | 692 | 1996 |
| Zero-shot learning by convex combination of semantic embeddings M Norouzi, T Mikolov, S Bengio, Y Singer, J Shlens, A Frome, GS Corrado, ... arXiv preprint arXiv:1312.5650, 2013 | 691 | 2013 |
