Koby Crammer

	2009
37		Partha Pratim Talukdar, Koby Crammer: New Regularized Algorithms for Transductive Learning. ECML/PKDD (2) 2009: 442-457
36		Ted Sandler, Lyle H. Ungar, Koby Crammer: Resolving Identity Uncertainty with Learned Random Walks. ICDM 2009: 457-465
	2008
35		Ron Bekkerman, Koby Crammer: One-Class Clustering in the Text Domain. EMNLP 2008: 41-50
34		Mark Dredze, Koby Crammer: Online Methods for Multi-Domain Learning and Adaptation. EMNLP 2008: 689-697
33		Koby Crammer, Partha Pratim Talukdar, Fernando Pereira: A rate-distortion one-class model and its applications to clustering. ICML 2008: 184-191
32		Mark Dredze, Koby Crammer, Fernando Pereira: Confidence-weighted linear classification. ICML 2008: 264-271
31		Koby Crammer, Mark Dredze, Fernando Pereira: Exact Convex Confidence-Weighted Learning. NIPS 2008: 345-352
30		Qian Liu, Koby Crammer, Fernando C. N. Pereira, David S. Roos: Reranking candidate gene models with cross-species comparison for improved gene prediction. BMC Bioinformatics 9: (2008)
29		Partha Pratim Talukdar, Marie Jacob, Muhammad Salman Mehmood, Koby Crammer, Zachary G. Ives, Fernando Pereira, Sudipto Guha: Learning to create data-integrating queries. PVLDB 1(1): 785-796 (2008)
	2007
28		John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman: Learning Bounds for Domain Adaptation. NIPS 2007
	2006
27		Linli Xu, Koby Crammer, Dale Schuurmans: Robust Support Vector Machine Training via Convex Outlier Ablation. AAAI 2006
26		Koby Crammer: Online Tracking of Linear Subspaces. COLT 2006: 438-452
25		Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira: Analysis of Representations for Domain Adaptation. NIPS 2006: 137-144
24		Koby Crammer, Michael J. Kearns, Jennifer Wortman: Learning from Multiple Sources. NIPS 2006: 321-328
23		Koby Crammer, Amir Globerson: Discriminative Learning via Semidefinite Probabilistic Models. UAI 2006
22		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
21		Ryan T. McDonald, Koby Crammer, Fernando C. N. Pereira: Online Large-Margin Training of Dependency Parsers. ACL 2005
20		Koby Crammer, Yoram Singer: Loss Bounds for Online Category Ranking. COLT 2005: 48-62
19		Ryan T. McDonald, Koby Crammer, Fernando Pereira: Flexible Text Segmentation with Structured Multilabel Classification. HLT/EMNLP 2005
18		Koby Crammer, Michael S. Kearns, Jennifer Wortman: Learning from Data of Variable Quality. NIPS 2005
17		Koby Crammer, Yoram Singer: Online Ranking by Projecting. Neural Computation 17(1): 145-175 (2005)
	2004
16		Koby Crammer, Gal Chechik: A needle in a haystack: local one-class optimization. ICML 2004
15		Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer: A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS 2004
	2003
14		Koby Crammer, Yoram Singer: Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT 2003: 388-402
13		Koby Crammer, Jaz S. Kandola, Yoram Singer: Online Classification on a Budget. NIPS 2003
12		Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer: Online Passive-Aggressive Algorithms. NIPS 2003
11		Koby Crammer, Yoram Singer: A Family of Additive Online Algorithms for Category Ranking. Journal of Machine Learning Research 3: 1025-1058 (2003)
10		Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. Journal of Machine Learning Research 3: 951-991 (2003)
	2002
9		Koby Crammer, Ran Gilad-Bachrach, Amir Navot, Naftali Tishby: Margin Analysis of the LVQ Algorithm. NIPS 2002: 462-469
8		Koby Crammer, Joseph Keshet, Yoram Singer: Kernel Design Using Boosting. NIPS 2002: 537-544
7		Koby Crammer, Yoram Singer: A new family of online algorithms for category ranking. SIGIR 2002: 151-158
6		Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. Machine Learning 47(2-3): 201-233 (2002)
	2001
5		Koby Crammer, Yoram Singer: Ultraconservative Online Algorithms for Multiclass Problems. COLT/EuroCOLT 2001: 99-115
4		Koby Crammer, Yoram Singer: Pranking with Ranking. NIPS 2001: 641-647
3		Koby Crammer, Yoram Singer: On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. Journal of Machine Learning Research 2: 265-292 (2001)
	2000
2		Koby Crammer, Yoram Singer: On the Learnability and Design of Output Codes for Multiclass Problems. COLT 2000: 35-46
1		Koby Crammer, Yoram Singer: Improved Output Coding for Classification Using Continuous Relaxation. NIPS 2000: 437-443

Coauthor Index

1	Ron Bekkerman	[35]
2	Shai Ben-David	[25]
3	John Blitzer	[25] [28]
4	Gal Chechik	[16]
5	Ofer Dekel	[12] [22]
6	Mark Dredze	[31] [32] [34]
7	Ran Gilad-Bachrach (Ran Bachrach)	[9]
8	Amir Globerson	[23]
9	Sudipto Guha	[29]
10	Zachary G. Ives	[29]
11	Marie Jacob	[29]
12	Jaz S. Kandola	[13]
13	Michael J. Kearns	[24]
14	Michael S. Kearns	[18]
15	Joseph Keshet	[8] [22]
16	Alex Kulesza	[28]
17	Qian Liu	[30]
18	Ryan T. McDonald	[19] [21]
19	Muhammad Salman Mehmood	[29]
20	Amir Navot	[9]
21	Rony Paz	[15]
22	Fernando Pereira	[19] [25] [28] [29] [31] [32] [33]
23	Fernando C. N. Pereira	[21] [30]
24	David S. Roos	[30]
25	Ted Sandler	[36]
26	Dale Schuurmans	[27]
27	Shai Shalev-Shwartz	[12] [22]
28	Lavi Shpigelman	[15]
29	Yoram Singer	[1] [2] [3] [4] [5] [6] [7] [8] [10] [11] [12] [13] [14] [15] [17] [20] [22]
30	Partha Pratim Talukdar	[29] [33] [37]
31	Naftali Tishby	[9]
32	Lyle H. Ungar	[36]
33	Eilon Vaadia	[15]
34	Jennifer Wortman	[18] [24] [28]
35	Linli Xu	[27]