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* | 2009 | |
---|---|---|

101 | EE | John Duchi, Yoram Singer: Boosting with structural sparsity. ICML 2009: 38 |

2008 | ||

100 | John C. Platt, Daphne Koller, Yoram Singer, Sam T. Roweis: 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 MIT Press 2008 | |

99 | EE | Shai Shalev-Shwartz, Yoram Singer: On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms. COLT 2008: 311-322 |

98 | EE | John Duchi,
Shai Shalev-Shwartz,
Yoram Singer,
Tushar Chandra:
Efficient projections onto the l_{1}-ball for learning in high dimensions.
ICML 2008: 272-279 |

97 | EE | Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Forgetron: A Kernel-Based Perceptron on a Budget. SIAM J. Comput. 37(5): 1342-1372 (2008) |

2007 | ||

96 | EE | Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik: Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. ICCV 2007: 1-8 |

95 | EE | Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. ICML 2007: 807-814 |

94 | EE | Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, D. Chazan: A Large Margin Algorithm for Speech-to-Phoneme and Music-to-Score Alignment. IEEE Transactions on Audio, Speech & Language Processing 15(8): 2373-2382 (2007) |

93 | EE | Shai Shalev-Shwartz, Yoram Singer: A primal-dual perspective of online learning algorithms. Machine Learning 69(2-3): 115-142 (2007) |

2006 | ||

92 | EE | Shai Shalev-Shwartz, Yoram Singer: Online Learning Meets Optimization in the Dual. COLT 2006: 423-437 |

91 | EE | Ofer Dekel, Philip M. Long, Yoram Singer: Online Multitask Learning. COLT 2006: 453-467 |

90 | EE | Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman: Online multiclass learning by interclass hypothesis sharing. ICML 2006: 313-320 |

89 | EE | Shai Shalev-Shwartz, Yoram Singer: Convex Repeated Games and Fenchel Duality. NIPS 2006: 1265-1272 |

88 | EE | Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer: Online Classification for Complex Problems Using Simultaneous Projections. NIPS 2006: 17-24 |

87 | EE | Ofer Dekel, Yoram Singer: Support Vector Machines on a Budget. NIPS 2006: 345-352 |

86 | EE | Andrea Frome, Yoram Singer, Jitendra Malik: Image Retrieval and Classification Using Local Distance Functions. NIPS 2006: 417-424 |

85 | EE | Shai Shalev-Shwartz, Yoram Singer: Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. Journal of Machine Learning Research 7: 1567-1599 (2006) |

84 | EE | Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer: Online Passive-Aggressive Algorithms. Journal of Machine Learning Research 7: 551-585 (2006) |

2005 | ||

83 | EE | Shai Shalev-Shwartz, Yoram Singer: A New Perspective on an Old Perceptron Algorithm. COLT 2005: 264-278 |

82 | EE | Koby Crammer, Yoram Singer: Loss Bounds for Online Category Ranking. COLT 2005: 48-62 |

81 | EE | Ofer Dekel, Yoram Singer: Data-Driven Online to Batch Conversions. NIPS 2005 |

80 | EE | Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. NIPS 2005 |

79 | EE | Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth epsiloon-Insensitive Regression by Loss Symmetrization. Journal of Machine Learning Research 6: 711-741 (2005) |

78 | EE | Koby Crammer, Yoram Singer: Online Ranking by Projecting. Neural Computation 17(1): 145-175 (2005) |

77 | EE | Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia: Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces. Neural Computation 17(3): 671-690 (2005) |

2004 | ||

76 | John Shawe-Taylor, Yoram Singer: Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings Springer 2004 | |

75 | EE | Ofer Dekel, Joseph Keshet, Yoram Singer: Large margin hierarchical classification. ICML 2004 |

74 | EE | Nir Krause, Yoram Singer: Leveraging the margin more carefully. ICML 2004 |

73 | EE | Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng: Online and batch learning of pseudo-metrics. ICML 2004 |

72 | EE | Shai Shalev-Shwartz, Joseph Keshet, Yoram Singer: Learning to Align Polyphonic Music. ISMIR 2004 |

71 | EE | Ofer Dekel, Joseph Keshet, Yoram Singer: An Online Algorithm for Hierarchical Phoneme Classification. MLMI 2004: 146-158 |

70 | EE | Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer: A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS 2004 |

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

2003 | ||

68 | EE | Koby Crammer, Yoram Singer: Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT 2003: 388-402 |

67 | EE | Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth e-Intensive Regression by Loss Symmetrization. COLT 2003: 433-447 |

66 | EE | Kristina Toutanova, Dan Klein, Christopher D. Manning, Yoram Singer: Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. HLT-NAACL 2003 |

65 | EE | Ofer Dekel, Christopher D. Manning, Yoram Singer: Log-Linear Models for Label Ranking. NIPS 2003 |

64 | EE | Koby Crammer, Jaz S. Kandola, Yoram Singer: Online Classification on a Budget. NIPS 2003 |

63 | EE | Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer: Online Passive-Aggressive Algorithms. NIPS 2003 |

62 | Eleazar Eskin, William Stafford Noble, Yoram Singer: Protein Family Classification Using Sparse Markov Transducers. Journal of Computational Biology 10(2): 187-214 (2003) | |

61 | EE | Koby Crammer, Yoram Singer: A Family of Additive Online Algorithms for Category Ranking. Journal of Machine Learning Research 3: 1025-1058 (2003) |

60 | EE | Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. Journal of Machine Learning Research 3: 951-991 (2003) |

59 | EE | Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer: An Efficient Boosting Algorithm for Combining Preferences. Journal of Machine Learning Research 4: 933-969 (2003) |

2002 | ||

58 | EE | Sanjoy Dasgupta, Elan Pavlov, Yoram Singer: An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. ALT 2002: 351-364 |

57 | EE | Ehud Ben-Reuven, Yoram Singer: Discriminative Binaural Sound Localization. NIPS 2002: 1229-1236 |

56 | EE | Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia: Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. NIPS 2002: 125-132 |

55 | EE | Koby Crammer, Joseph Keshet, Yoram Singer: Kernel Design Using Boosting. NIPS 2002: 537-544 |

54 | EE | Ofer Dekel, Yoram Singer: Multiclass Learning by Probabilistic Embeddings. NIPS 2002: 945-952 |

53 | EE | Koby Crammer, Yoram Singer: A new family of online algorithms for category ranking. SIGIR 2002: 151-158 |

52 | EE | Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer: Robust temporal and spectral modeling for query By melody. SIGIR 2002: 331-338 |

51 | Eleazar Eskin, William Stafford Noble, Yoram Singer: Using Substitution Matrices to Estimate Probability Distributions for Biological Sequences. Journal of Computational Biology 9(6): 775-792 (2002) | |

50 | Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. Machine Learning 47(2-3): 201-233 (2002) | |

49 | Michael Collins, Robert E. Schapire, Yoram Singer: Logistic Regression, AdaBoost and Bregman Distances. Machine Learning 48(1-3): 253-285 (2002) | |

2001 | ||

48 | EE | Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. COLT/EuroCOLT 2001: 99-115 |

47 | Eleazar Eskin, William Noble Grundy, Yoram Singer: Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences. ISMB (Supplement of Bioinformatics) 2001: 65-73 | |

46 | EE | Koby Crammer, Yoram Singer: Pranking with Ranking. NIPS 2001: 641-647 |

45 | EE | Koby Crammer, Yoram Singer: On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. Journal of Machine Learning Research 2: 265-292 (2001) |

44 | Yoram Singer: Guest Editor's Introduction. Machine Learning 43(3): 71-172 (2001) | |

2000 | ||

43 | EE | Raj D. Iyer, David D. Lewis, Robert E. Schapire, Yoram Singer, Amit Singhal: Boosting for Document Routing. CIKM 2000: 70-77 |

42 | Michael Collins, Robert E. Schapire, Yoram Singer: Logistic Regression, AdaBoost and Bregman Distances. COLT 2000: 158-169 | |

41 | Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. COLT 2000: 35-46 | |

40 | Peter Ju, Leslie Pack Kaelbling, Yoram Singer: State-based Classification of Finger Gestures from Electromyographic Signals. ICML 2000: 439-446 | |

39 | Erin L. Allwein, Robert E. Schapire, Yoram Singer: Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. ICML 2000: 9-16 | |

38 | Eleazar Eskin, William Noble Grundy, Yoram Singer: Protein Family Classification Using Sparse Markov Transducers. ISMB 2000: 134-145 | |

37 | Koby Crammer, Yoram Singer: Improved Output Coding for Classification Using Continuous Relaxation. NIPS 2000: 437-443 | |

36 | EE | Erin L. Allwein, Robert E. Schapire, Yoram Singer: Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. Journal of Machine Learning Research 1: 113-141 (2000) |

35 | Robert E. Schapire, Yoram Singer: BoosTexter: A Boosting-based System for Text Categorization. Machine Learning 39(2/3): 135-168 (2000) | |

1999 | ||

34 | William W. Cohen, Yoram Singer: A Simple, Fast, and Effictive Rule Learner. AAAI/IAAI 1999: 335-342 | |

33 | EE | Yoram Singer: Leveraged Vector Machines. NIPS 1999: 610-616 |

32 | EE | William W. Cohen, Yoram Singer: Context-Sensitive Learning Methods for Text Categorization. ACM Trans. Inf. Syst. 17(2): 141-173 (1999) |

31 | EE | William W. Cohen, Robert E. Schapire, Yoram Singer: Learning to Order Things. J. Artif. Intell. Res. (JAIR) 10: 243-270 (1999) |

30 | Fernando C. N. Pereira, Yoram Singer: An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. Machine Learning 36(3): 183-199 (1999) | |

29 | Robert E. Schapire, Yoram Singer: Improved Boosting Algorithms Using Confidence-rated Predictions. Machine Learning 37(3): 297-336 (1999) | |

1998 | ||

28 | EE | Robert E. Schapire, Yoram Singer: Improved Boosting Algorithms using Confidence-Rated Predictions. COLT 1998: 80-91 |

27 | Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer: An Efficient Boosting Algorithm for Combining Preferences. ICML 1998: 170-178 | |

26 | EE | Nir Friedman, Yoram Singer: Efficient Bayesian Parameter Estimation in Large Discrete Domains. NIPS 1998: 417-423 |

25 | EE | Yoram Singer, Manfred K. Warmuth: Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy. NIPS 1998: 578-584 |

24 | EE | Robert E. Schapire, Yoram Singer, Amit Singhal: Boosting and Rocchio Applied to Text Filtering. SIGIR 1998: 215-223 |

23 | EE | Yoram Singer: Switching Portfolios. UAI 1998: 488-495 |

22 | Dana Ron, Yoram Singer, Naftali Tishby: On the Learnability and Usage of Acyclic Probabilistic Finite Automata. J. Comput. Syst. Sci. 56(2): 133-152 (1998) | |

21 | Shai Fine, Yoram Singer, Naftali Tishby: The Hierarchical Hidden Markov Model: Analysis and Applications. Machine Learning 32(1): 41-62 (1998) | |

1997 | ||

20 | EE | Fernando C. N. Pereira, Yoram Singer: An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. COLT 1997: 114-121 |

19 | William W. Cohen, Robert E. Schapire, Yoram Singer: Learning to Order Things. NIPS 1997 | |

18 | Yoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer: Shared Context Probabilistic Transducers. NIPS 1997 | |

17 | EE | Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: Using and Combining Predictors That Specialize. STOC 1997: 334-343 |

16 | EE | Eric Bauer, Daphne Koller, Yoram Singer: Update Rules for Parameter Estimation in Bayesian Networks. UAI 1997: 3-13 |

15 | EE | Yoram Singer: Switching Portfolios. Int. J. Neural Syst. 8(4): 445-455 (1997) |

14 | David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: A Comparison of New and Old Algorithms for a Mixture Estimation Problem. Machine Learning 27(1): 97-119 (1997) | |

13 | EE | Yoram Singer: Adaptive Mixtures of Probabilistic Transducers. Neural Computation 9(8): 1711-1733 (1997) |

1996 | ||

12 | David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: On-Line Portfolio Selection Using Multiplicative Updates. ICML 1996: 243-251 | |

11 | EE | Yoram Singer, Manfred K. Warmuth: Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. NIPS 1996: 641-647 |

10 | EE | William W. Cohen, Yoram Singer: Context-sensitive Learning Methods for Text Categorization. SIGIR 1996: 307-315 |

9 | EE | Fernando C. N. Pereira, Yoram Singer, Naftali Tishby: Beyond Word N-Grams CoRR cmp-lg/9607016: (1996) |

8 | Dana Ron, Yoram Singer, Naftali Tishby: The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length. Machine Learning 25(2-3): 117-149 (1996) | |

1995 | ||

7 | EE | Dana Ron, Yoram Singer, Naftali Tishby: On the Learnability and Usage of Acyclic Probabilistic Finite Automata. COLT 1995: 31-40 |

6 | EE | David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth: A Comparison of New and Old Algorithms for a Mixture Estimation Problem. COLT 1995: 69-78 |

5 | EE | Yoram Singer: Adaptive Mixture of Probabilistic Transducers. NIPS 1995: 381-387 |

1994 | ||

4 | Hinrich Schütze, Yoram Singer: Part-of-Speech Tagging using a Variable Memory Markov Model. ACL 1994: 181-187 | |

3 | EE | Dana Ron, Yoram Singer, Naftali Tishby: Learning Probabilistic Automata with Variable Memory Length. COLT 1994: 35-46 |

1993 | ||

2 | EE | Dana Ron, Yoram Singer, Naftali Tishby: The Power of Amnesia. NIPS 1993: 176-183 |

1 | EE | Yoram Singer, Naftali Tishby: Decoding Cursive Scripts. NIPS 1993: 833-840 |