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*2009
101EEJohn 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
99EEShai Shalev-Shwartz, Yoram Singer: On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms. COLT 2008: 311-322
98EEJohn Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra: Efficient projections onto the l1-ball for learning in high dimensions. ICML 2008: 272-279
97EEOfer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Forgetron: A Kernel-Based Perceptron on a Budget. SIAM J. Comput. 37(5): 1342-1372 (2008)
2007
96EEAndrea Frome, Yoram Singer, Fei Sha, Jitendra Malik: Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. ICCV 2007: 1-8
95EEShai Shalev-Shwartz, Yoram Singer, Nathan Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. ICML 2007: 807-814
94EEJoseph 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)
93EEShai Shalev-Shwartz, Yoram Singer: A primal-dual perspective of online learning algorithms. Machine Learning 69(2-3): 115-142 (2007)
2006
92EEShai Shalev-Shwartz, Yoram Singer: Online Learning Meets Optimization in the Dual. COLT 2006: 423-437
91EEOfer Dekel, Philip M. Long, Yoram Singer: Online Multitask Learning. COLT 2006: 453-467
90EEMichael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman: Online multiclass learning by interclass hypothesis sharing. ICML 2006: 313-320
89EEShai Shalev-Shwartz, Yoram Singer: Convex Repeated Games and Fenchel Duality. NIPS 2006: 1265-1272
88EEYonatan Amit, Shai Shalev-Shwartz, Yoram Singer: Online Classification for Complex Problems Using Simultaneous Projections. NIPS 2006: 17-24
87EEOfer Dekel, Yoram Singer: Support Vector Machines on a Budget. NIPS 2006: 345-352
86EEAndrea Frome, Yoram Singer, Jitendra Malik: Image Retrieval and Classification Using Local Distance Functions. NIPS 2006: 417-424
85EEShai Shalev-Shwartz, Yoram Singer: Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. Journal of Machine Learning Research 7: 1567-1599 (2006)
84EEKoby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer: Online Passive-Aggressive Algorithms. Journal of Machine Learning Research 7: 551-585 (2006)
2005
83EEShai Shalev-Shwartz, Yoram Singer: A New Perspective on an Old Perceptron Algorithm. COLT 2005: 264-278
82EEKoby Crammer, Yoram Singer: Loss Bounds for Online Category Ranking. COLT 2005: 48-62
81EEOfer Dekel, Yoram Singer: Data-Driven Online to Batch Conversions. NIPS 2005
80EEOfer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. NIPS 2005
79EEOfer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth epsiloon-Insensitive Regression by Loss Symmetrization. Journal of Machine Learning Research 6: 711-741 (2005)
78EEKoby Crammer, Yoram Singer: Online Ranking by Projecting. Neural Computation 17(1): 145-175 (2005)
77EELavi 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
75EEOfer Dekel, Joseph Keshet, Yoram Singer: Large margin hierarchical classification. ICML 2004
74EENir Krause, Yoram Singer: Leveraging the margin more carefully. ICML 2004
73EEShai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng: Online and batch learning of pseudo-metrics. ICML 2004
72EEShai Shalev-Shwartz, Joseph Keshet, Yoram Singer: Learning to Align Polyphonic Music. ISMIR 2004
71EEOfer Dekel, Joseph Keshet, Yoram Singer: An Online Algorithm for Hierarchical Phoneme Classification. MLMI 2004: 146-158
70EELavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer: A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS 2004
69EEOfer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. NIPS 2004
2003
68EEKoby Crammer, Yoram Singer: Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT 2003: 388-402
67EEOfer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth e-Intensive Regression by Loss Symmetrization. COLT 2003: 433-447
66EEKristina Toutanova, Dan Klein, Christopher D. Manning, Yoram Singer: Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. HLT-NAACL 2003
65EEOfer Dekel, Christopher D. Manning, Yoram Singer: Log-Linear Models for Label Ranking. NIPS 2003
64EEKoby Crammer, Jaz S. Kandola, Yoram Singer: Online Classification on a Budget. NIPS 2003
63EEShai 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)
61EEKoby Crammer, Yoram Singer: A Family of Additive Online Algorithms for Category Ranking. Journal of Machine Learning Research 3: 1025-1058 (2003)
60EEKoby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. Journal of Machine Learning Research 3: 951-991 (2003)
59EEYoav 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
58EESanjoy Dasgupta, Elan Pavlov, Yoram Singer: An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. ALT 2002: 351-364
57EEEhud Ben-Reuven, Yoram Singer: Discriminative Binaural Sound Localization. NIPS 2002: 1229-1236
56EELavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia: Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. NIPS 2002: 125-132
55EEKoby Crammer, Joseph Keshet, Yoram Singer: Kernel Design Using Boosting. NIPS 2002: 537-544
54EEOfer Dekel, Yoram Singer: Multiclass Learning by Probabilistic Embeddings. NIPS 2002: 945-952
53EEKoby Crammer, Yoram Singer: A new family of online algorithms for category ranking. SIGIR 2002: 151-158
52EEShai 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
48EEKoby 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
46EEKoby Crammer, Yoram Singer: Pranking with Ranking. NIPS 2001: 641-647
45EEKoby 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
43EERaj 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
36EEErin 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
33EEYoram Singer: Leveraged Vector Machines. NIPS 1999: 610-616
32EEWilliam W. Cohen, Yoram Singer: Context-Sensitive Learning Methods for Text Categorization. ACM Trans. Inf. Syst. 17(2): 141-173 (1999)
31EEWilliam 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
28EERobert 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
26EENir Friedman, Yoram Singer: Efficient Bayesian Parameter Estimation in Large Discrete Domains. NIPS 1998: 417-423
25EEYoram Singer, Manfred K. Warmuth: Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy. NIPS 1998: 578-584
24EERobert E. Schapire, Yoram Singer, Amit Singhal: Boosting and Rocchio Applied to Text Filtering. SIGIR 1998: 215-223
23EEYoram 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
20EEFernando 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
17EEYoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: Using and Combining Predictors That Specialize. STOC 1997: 334-343
16EEEric Bauer, Daphne Koller, Yoram Singer: Update Rules for Parameter Estimation in Bayesian Networks. UAI 1997: 3-13
15EEYoram 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)
13EEYoram 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
11EEYoram Singer, Manfred K. Warmuth: Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. NIPS 1996: 641-647
10EEWilliam W. Cohen, Yoram Singer: Context-sensitive Learning Methods for Text Categorization. SIGIR 1996: 307-315
9EEFernando 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
7EEDana Ron, Yoram Singer, Naftali Tishby: On the Learnability and Usage of Acyclic Probabilistic Finite Automata. COLT 1995: 31-40
6EEDavid 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
5EEYoram 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
3EEDana Ron, Yoram Singer, Naftali Tishby: Learning Probabilistic Automata with Variable Memory Length. COLT 1994: 35-46
1993
2EEDana Ron, Yoram Singer, Naftali Tishby: The Power of Amnesia. NIPS 1993: 176-183
1EEYoram Singer, Naftali Tishby: Decoding Cursive Scripts. NIPS 1993: 833-840

Coauthor Index

1Erin L. Allwein [36] [39]
2Yonatan Amit [88]
3Eric Bauer [16]
4Ehud Ben-Reuven [57]
5Samy Bengio [18]
6Yoshua Bengio [18]
7Tushar Chandra [98]
8D. Chazan [94]
9William W. Cohen [10] [19] [31] [32] [34]
10Michael Collins [42] [49]
11Koby Crammer [37] [41] [45] [46] [48] [50] [53] [55] [60] [61] [63] [64] [68] [70] [78] [82] [84]
12Sanjoy Dasgupta [58]
13Ofer Dekel [54] [63] [65] [67] [69] [71] [75] [79] [80] [81] [84] [87] [91] [97]
14Shlomo Dubnov [52]
15John Duchi [98] [101]
16Eleazar Eskin [38] [47] [51] [62]
17Shai Fine [21]
18Michael Fink [90]
19Yoav Freund [17] [27] [59]
20Nir Friedman [26] [52]
21Andrea Frome [86] [96]
22William Noble Grundy [38] [47]
23David P. Helmbold [6] [12] [14]
24Jean-Franc Isabelle [18]
25Raj D. Iyer [27] [43] [59]
26Peter Ju [40]
27Leslie Pack Kaelbling [40]
28Jaz S. Kandola [64]
29Joseph Keshet [55] [71] [72] [75] [84] [94]
30Dan Klein [66]
31Daphne Koller [16] [100]
32Nir Krause [74]
33David D. Lewis [43]
34Philip M. Long [91]
35Jitendra Malik [86] [96]
36Christopher D. Manning [65] [66]
37Andrew Y. Ng [73]
38William Stafford Noble [51] [62]
39Elan Pavlov [58]
40Rony Paz [56] [70] [77]
41Fernando C. N. Pereira [9] [20] [30]
42John C. Platt [100]
43Dana Ron [2] [3] [7] [8] [22]
44Sam T. Roweis [100]
45Robert E. Schapire [6] [12] [14] [17] [19] [24] [27] [28] [29] [31] [35] [36] [39] [42] [43] [49] [59]
46Hinrich Schütze [4]
47Fei Sha [96]
48Shai Shalev-Shwartz [52] [63] [67] [69] [72] [73] [79] [80] [83] [84] [85] [88] [89] [90] [92] [93] [94] [95] [97] [98] [99]
49John Shawe-Taylor [76]
50Lavi Shpigelman [56] [70] [77]
51Amit Singhal [24] [43]
52Nathan Srebro [95]
53Naftali Tishby [1] [2] [3] [7] [8] [9] [21] [22]
54Kristina Toutanova [66]
55Shimon Ullman [90]
56Eilon Vaadia [56] [70] [77]
57Manfred K. Warmuth [6] [11] [12] [14] [17] [25]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)