Yoram Singer

	2011
119		Moshe Dubiner, Yoram Singer: Entire Relaxation Path for Maximum Entropy Problems. EMNLP 2011: 941-948
118		William W. Cohen, Robert E. Schapire, Yoram Singer: Learning to Order Things CoRR abs/1105.5464: (2011)
117		John C. Duchi, Elad Hazan, Yoram Singer: Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. Journal of Machine Learning Research 12: 2121-2159 (2011)
116		Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter: Pegasos: primal estimated sub-gradient solver for SVM. Math. Program. 127(1): 3-30 (2011)
	2010
115		John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari: Composite Objective Mirror Descent. COLT 2010: 14-26
114		John C. Duchi, Elad Hazan, Yoram Singer: Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. COLT 2010: 257-269
113		Shai Shalev-Shwartz, Yoram Singer: On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms. Machine Learning 80(2-3): 141-163 (2010)
	2009
112		John C. Duchi, Yoram Singer: Boosting with structural sparsity. ICML 2009: 38
111		John C. Duchi, Yoram Singer: Efficient Learning using Forward-Backward Splitting. NIPS 2009: 495-503
110		Samy Bengio, Fernando C. N. Pereira, Yoram Singer, Dennis Strelow: Group Sparse Coding. NIPS 2009: 82-89
109		Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Individual sequence prediction using memory-efficient context trees. IEEE Transactions on Information Theory 55(11): 5251-5262 (2009)
108		John C. Duchi, Yoram Singer: Efficient Online and Batch Learning Using Forward Backward Splitting. Journal of Machine Learning Research 10: 2899-2934 (2009)
	2008
107		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 Curran Associates, Inc. 2008
106		Shai Shalev-Shwartz, Yoram Singer: On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms. COLT 2008: 311-322
105		John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra: Efficient projections onto the l1-ball for learning in high dimensions. ICML 2008: 272-279
104		Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer: Online Learning of Complex Prediction Problems Using Simultaneous Projections. Journal of Machine Learning Research 9: 1399-1435 (2008)
103		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
102		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
101		Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. ICML 2007: 807-814
100		Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Dan 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)
99		Ofer Dekel, Philip M. Long, Yoram Singer: Online Learning of Multiple Tasks with a Shared Loss. Journal of Machine Learning Research 8: 2233-2264 (2007)
98		Yonatan Amit, Ofer Dekel, Yoram Singer: A Boosting Algorithm for Label Covering in Multilabel Problems. Journal of Machine Learning Research - Proceedings Track 2: 27-34 (2007)
97		Shai Shalev-Shwartz, Yoram Singer: A Unified Algorithmic Approach for Efficient Online Label Ranking. Journal of Machine Learning Research - Proceedings Track 2: 452-459 (2007)
96		Shai Shalev-Shwartz, Yoram Singer: A primal-dual perspective of online learning algorithms. Machine Learning 69(2-3): 115-142 (2007)
	2006
95		Shai Shalev-Shwartz, Yoram Singer: Online Learning Meets Optimization in the Dual. COLT 2006: 423-437
94		Ofer Dekel, Philip M. Long, Yoram Singer: Online Multitask Learning. COLT 2006: 453-467
93		Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman: Online multiclass learning by interclass hypothesis sharing. ICML 2006: 313-320
92		Joseph Keshet, Shai Shalev-Shwartz, Samy Bengio, Yoram Singer, Dan Chazan: Discriminative kernel-based phoneme sequence recognition. INTERSPEECH 2006
91		Shai Shalev-Shwartz, Yoram Singer: Convex Repeated Games and Fenchel Duality. NIPS 2006: 1265-1272
90		Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer: Online Classification for Complex Problems Using Simultaneous Projections. NIPS 2006: 17-24
89		Ofer Dekel, Yoram Singer: Support Vector Machines on a Budget. NIPS 2006: 345-352
88		Andrea Frome, Yoram Singer, Jitendra Malik: Image Retrieval and Classification Using Local Distance Functions. NIPS 2006: 417-424
87		Shai Shalev-Shwartz, Yoram Singer: Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. Journal of Machine Learning Research 7: 1567-1599 (2006)
86		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
85		Shai Shalev-Shwartz, Yoram Singer: A New Perspective on an Old Perceptron Algorithm. COLT 2005: 264-278
84		Koby Crammer, Yoram Singer: Loss Bounds for Online Category Ranking. COLT 2005: 48-62
83		Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer, Dan Chazan: Phoneme alignment based on discriminative learning. INTERSPEECH 2005: 2961-2964
82		Ofer Dekel, Yoram Singer: Data-Driven Online to Batch Conversions. NIPS 2005
81		Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. NIPS 2005
80		Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth epsiloon-Insensitive Regression by Loss Symmetrization. Journal of Machine Learning Research 6: 711-741 (2005)
79		Koby Crammer, Yoram Singer: Online Ranking by Projecting. Neural Computation 17(1): 145-175 (2005)
78		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
77		John Shawe-Taylor, Yoram Singer: Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings Springer 2004
76		Ofer Dekel, Joseph Keshet, Yoram Singer: Large margin hierarchical classification. ICML 2004
75		Nir Krause, Yoram Singer: Leveraging the margin more carefully. ICML 2004
74		Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng: Online and batch learning of pseudo-metrics. ICML 2004
73		Shai Shalev-Shwartz, Joseph Keshet, Yoram Singer: Learning to Align Polyphonic Music. ISMIR 2004
72		Ofer Dekel, Joseph Keshet, Yoram Singer: An Online Algorithm for Hierarchical Phoneme Classification. MLMI 2004: 146-158
71		Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer: A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS 2004
70		Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. NIPS 2004
	2003
69		Koby Crammer, Yoram Singer: Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT 2003: 388-402
68		Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth e-Intensive Regression by Loss Symmetrization. COLT 2003: 433-447
67		Kristina Toutanova, Dan Klein, Christopher D. Manning, Yoram Singer: Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. HLT-NAACL 2003
66		Ofer Dekel, Christopher D. Manning, Yoram Singer: Log-Linear Models for Label Ranking. NIPS 2003
65		Koby Crammer, Jaz S. Kandola, Yoram Singer: Online Classification on a Budget. NIPS 2003
64		Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer: Online Passive-Aggressive Algorithms. NIPS 2003
63		Eleazar Eskin, William Stafford Noble, Yoram Singer: Protein Family Classification Using Sparse Markov Transducers. Journal of Computational Biology 10(2): 187-214 (2003)
62		Koby Crammer, Yoram Singer: A Family of Additive Online Algorithms for Category Ranking. Journal of Machine Learning Research 3: 1025-1058 (2003)
61		Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. Journal of Machine Learning Research 3: 951-991 (2003)
60		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
59		Sanjoy Dasgupta, Elan Pavlov, Yoram Singer: An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. ALT 2002: 351-364
58		Ehud Ben-Reuven, Yoram Singer: Discriminative Binaural Sound Localization. NIPS 2002: 1229-1236
57		Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia: Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. NIPS 2002: 125-132
56		Koby Crammer, Joseph Keshet, Yoram Singer: Kernel Design Using Boosting. NIPS 2002: 537-544
55		Ofer Dekel, Yoram Singer: Multiclass Learning by Probabilistic Embeddings. NIPS 2002: 945-952
54		Koby Crammer, Yoram Singer: A new family of online algorithms for category ranking. SIGIR 2002: 151-158
53		Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer: Robust temporal and spectral modeling for query By melody. SIGIR 2002: 331-338
52		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)
51		Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. Machine Learning 47(2-3): 201-233 (2002)
50		Michael Collins, Robert E. Schapire, Yoram Singer: Logistic Regression, AdaBoost and Bregman Distances. Machine Learning 48(1-3): 253-285 (2002)
	2001
49		Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. COLT/EuroCOLT 2001: 99-115
48		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
47		Koby Crammer, Yoram Singer: Pranking with Ranking. NIPS 2001: 641-647
46		Koby Crammer, Yoram Singer: On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. Journal of Machine Learning Research 2: 265-292 (2001)
45		Yoram Singer: Guest Editor's Introduction. Machine Learning 43(3): 71-172 (2001)
	2000
44		Raj D. Iyer, David D. Lewis, Robert E. Schapire, Yoram Singer, Amit Singhal: Boosting for Document Routing. CIKM 2000: 70-77
43		Michael Collins, Robert E. Schapire, Yoram Singer: Logistic Regression, AdaBoost and Bregman Distances. COLT 2000: 158-169
42		Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. COLT 2000: 35-46
41		Peter Ju, Leslie Pack Kaelbling, Yoram Singer: State-based Classification of Finger Gestures from Electromyographic Signals. ICML 2000: 439-446
40		Erin L. Allwein, Robert E. Schapire, Yoram Singer: Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. ICML 2000: 9-16
39		Eleazar Eskin, William Noble Grundy, Yoram Singer: Protein Family Classification Using Sparse Markov Transducers. ISMB 2000: 134-145
38		Koby Crammer, Yoram Singer: Improved Output Coding for Classification Using Continuous Relaxation. NIPS 2000: 437-443
37		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)
36		Robert E. Schapire, Yoram Singer: BoosTexter: A Boosting-based System for Text Categorization. Machine Learning 39(2/3): 135-168 (2000)
	1999
35		William W. Cohen, Yoram Singer: A Simple, Fast, and Effictive Rule Learner. AAAI/IAAI 1999: 335-342
34		Yoram Singer: Leveraged Vector Machines. NIPS 1999: 610-616
33		William W. Cohen, Yoram Singer: Context-Sensitive Learning Methods for Text Categorization. ACM Trans. Inf. Syst. 17(2): 141-173 (1999)
32		William W. Cohen, Robert E. Schapire, Yoram Singer: Learning to Order Things. J. Artif. Intell. Res. (JAIR) 10: 243-270 (1999)
31		Fernando C. N. Pereira, Yoram Singer: An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. Machine Learning 36(3): 183-199 (1999)
30		Robert E. Schapire, Yoram Singer: Improved Boosting Algorithms Using Confidence-rated Predictions. Machine Learning 37(3): 297-336 (1999)
	1998
29		Robert E. Schapire, Yoram Singer: Improved Boosting Algorithms using Confidence-Rated Predictions. COLT 1998: 80-91
28		Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer: An Efficient Boosting Algorithm for Combining Preferences. ICML 1998: 170-178
27		Nir Friedman, Yoram Singer: Efficient Bayesian Parameter Estimation in Large Discrete Domains. NIPS 1998: 417-423
26		Yoram Singer, Manfred K. Warmuth: Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy. NIPS 1998: 578-584
25		Robert E. Schapire, Yoram Singer, Amit Singhal: Boosting and Rocchio Applied to Text Filtering. SIGIR 1998: 215-223
24		Yoram Singer: Switching Portfolios. UAI 1998: 488-495
23		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)
22		Shai Fine, Yoram Singer, Naftali Tishby: The Hierarchical Hidden Markov Model: Analysis and Applications. Machine Learning 32(1): 41-62 (1998)
	1997
21		Fernando C. N. Pereira, Yoram Singer: An Efficient Extension to Mixture Techniques for Prediction and Decision Trees. COLT 1997: 114-121
20		William W. Cohen, Robert E. Schapire, Yoram Singer: Learning to Order Things. NIPS 1997
19		Yoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer: Shared Context Probabilistic Transducers. NIPS 1997
18		Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: Using and Combining Predictors That Specialize. STOC 1997: 334-343
17		Eric Bauer, Daphne Koller, Yoram Singer: Update Rules for Parameter Estimation in Bayesian Networks. UAI 1997: 3-13
16		Yoram Singer: Switching Portfolios. Int. J. Neural Syst. 8(4): 445-455 (1997)
15		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)
14		Yoram Singer: Adaptive Mixtures of Probabilistic Transducers. Neural Computation 9(8): 1711-1733 (1997)
	1996
13		David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth: On-Line Portfolio Selection Using Multiplicative Updates. ICML 1996: 243-251
12		Yoram Singer, Manfred K. Warmuth: Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. NIPS 1996: 641-647
11		William W. Cohen, Yoram Singer: Context-sensitive Learning Methods for Text Categorization. SIGIR 1996: 307-315
10		Fernando C. N. Pereira, Yoram Singer, Naftali Tishby: Beyond Word N-Grams CoRR cmp-lg/9607016: (1996)
9		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
8		Dana Ron, Yoram Singer, Naftali Tishby: On the Learnability and Usage of Acyclic Probabilistic Finite Automata. COLT 1995: 31-40
7		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
6		Yoram Singer: Adaptive Mixture of Probabilistic Transducers. NIPS 1995: 381-387
	1994
5		Hinrich Schütze, Yoram Singer: Part-of-Speech Tagging using a Variable Memory Markov Model. ACL 1994: 181-187
4		Dana Ron, Yoram Singer, Naftali Tishby: Learning Probabilistic Automata with Variable Memory Length. COLT 1994: 35-46
3		Yoram Singer, Naftali Tishby: Dynamical encoding of cursive handwriting. Biological Cybernetics 71(3): 227-237 (1994)
	1993
2		Dana Ron, Yoram Singer, Naftali Tishby: The Power of Amnesia. NIPS 1993: 176-183
1		Yoram Singer, Naftali Tishby: Decoding Cursive Scripts. NIPS 1993: 833-840

Coauthor Index

1	Erin L. Allwein	[37] [40]
2	Yonatan Amit	[90] [98] [104]
3	Eric Bauer	[17]
4	Ehud Ben-Reuven	[58]
5	Samy Bengio	[19] [92] [110]
6	Yoshua Bengio	[19]
7	Tushar Chandra	[105]
8	Dan Chazan	[83] [92] [100]
9	William W. Cohen	[11] [20] [32] [33] [35] [118]
10	Michael Collins	[43] [50]
11	Andrew Cotter	[116]
12	Koby Crammer	[38] [42] [46] [47] [49] [51] [54] [56] [61] [62] [64] [65] [69] [71] [79] [84] [86]
13	Sanjoy Dasgupta	[59]
14	Ofer Dekel	[55] [64] [66] [68] [70] [72] [76] [80] [81] [82] [86] [89] [94] [98] [99] [103] [109]
15	Moshe Dubiner	[119]
16	Shlomo Dubnov	[53]
17	John C. Duchi	[105] [108] [111] [112] [114] [115] [117]
18	Eleazar Eskin	[39] [48] [52] [63]
19	Shai Fine	[22]
20	Michael Fink	[93]
21	Yoav Freund	[18] [28] [60]
22	Nir Friedman	[27] [53]
23	Andrea Frome	[88] [102]
24	William Noble Grundy	[39] [48]
25	Elad Hazan	[114] [117]
26	David P. Helmbold	[7] [13] [15]
27	Jean-Franc Isabelle	[19]
28	Raj D. Iyer	[28] [44] [60]
29	Peter Ju	[41]
30	Leslie Pack Kaelbling	[41]
31	Jaz S. Kandola	[65]
32	Joseph Keshet	[56] [72] [73] [76] [83] [86] [92] [100]
33	Dan Klein	[67]
34	Daphne Koller	[17] [107]
35	Nir Krause	[75]
36	David D. Lewis	[44]
37	Philip M. Long	[94] [99]
38	Jitendra Malik	[88] [102]
39	Christopher D. Manning	[66] [67]
40	Andrew Y. Ng	[74]
41	William Stafford Noble	[52] [63]
42	Elan Pavlov	[59]
43	Rony Paz	[57] [71] [78]
44	Fernando C. N. Pereira	[10] [21] [31] [110]
45	John C. Platt	[107]
46	Dana Ron	[2] [4] [8] [9] [23]
47	Sam T. Roweis	[107]
48	Robert E. Schapire	[7] [13] [15] [18] [20] [25] [28] [29] [30] [32] [36] [37] [40] [43] [44] [50] [60] [118]
49	Hinrich Schütze	[5]
50	Fei Sha	[102]
51	Shai Shalev-Shwartz	[53] [64] [68] [70] [73] [74] [80] [81] [83] [85] [86] [87] [90] [91] [92] [93] [95] [96] [97] [100] [101] [103] [104] [105] [106] [109] [113] [115] [116]
52	John Shawe-Taylor	[77]
53	Lavi Shpigelman	[57] [71] [78]
54	Amit Singhal	[25] [44]
55	Nathan Srebro (Nati Srebro)	[101] [116]
56	Dennis Strelow	[110]
57	Ambuj Tewari	[115]
58	Naftali Tishby	[1] [2] [3] [4] [8] [9] [10] [22] [23]
59	Kristina Toutanova	[67]
60	Shimon Ullman	[93]
61	Eilon Vaadia	[57] [71] [78]
62	Manfred K. Warmuth	[7] [12] [13] [15] [18] [26]

Colors in the list of coauthors

Last update Fri May 25 01:42:58 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page