Gal Elidan

	2009
20		Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller: Shape-Based Object Localization for Descriptive Classification. International Journal of Computer Vision 84(1): 40-62 (2009)
	2008
19		Gal Elidan, Stephen Gould: Learning Bounded Treewidth Bayesian Networks. NIPS 2008: 417-424
18		Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller: Shape-Based Object Localization for Descriptive Classification. NIPS 2008: 633-640
17		Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller: Convex Point Estimation using Undirected Bayesian Transfer Hierarchies. UAI 2008: 179-186
16		Stephen Gould, Jim Rodgers, David Cohen, Gal Elidan, Daphne Koller: Multi-Class Segmentation with Relative Location Prior. International Journal of Computer Vision 80(3): 300-316 (2008)
	2006
15		Gal Elidan, Geremy Heitz, Daphne Koller: Learning Object Shape: From Drawings to Images. CVPR (2) 2006: 2064-2071
14		Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller: Max-margin classification of incomplete data. NIPS 2006: 233-240
13		John Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller: Using Combinatorial Optimization within Max-Product Belief Propagation. NIPS 2006: 369-376
12		Gal Elidan, Ian McGraw, Daphne Koller: Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing. UAI 2006
11		Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman: Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach. Journal of Computational Biology 13(2): 145-164 (2006)
	2005
10		Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman: Towards an Integrated Protein-Protein Interaction Network. RECOMB 2005: 14-30
9		Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman: Y. Barash, G. Elidan, T. Kaplan, , N. Friedman. Bioinformatics 21(5): 596-600 (2005)
8		Gal Elidan, Nir Friedman: Learning Hidden Variable Networks: The Information Bottleneck Approach. Journal of Machine Learning Research 6: 81-127 (2005)
	2004
7		Iftach Nachman, Gal Elidan, Nir Friedman: "Ideal Parent" Structure Learning for Continuous Variable Networks. UAI 2004: 400-409
	2003
6		Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan: Modeling dependencies in protein-DNA binding sites. RECOMB 2003: 28-37
5		Gal Elidan, Nir Friedman: The Information Bottleneck EM Algorithm. UAI 2003: 200-208
	2002
4		Gal Elidan, Matan Ninio, Nir Friedman, Dale Shuurmans: Data Perturbation for Escaping Local Maxima in Learning. AAAI/IAAI 2002: 132-139
	2001
3		Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman: Inferring subnetworks from perturbed expression profiles. ISMB (Supplement of Bioinformatics) 2001: 215-224
2		Gal Elidan, Nir Friedman: Learning the Dimensionality of Hidden Variables. UAI 2001: 144-151
	2000
1		Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller: Discovering Hidden Variables: A Structure-Based Approach. NIPS 2000: 479-485

Coauthor Index

1	Pieter Abbeel	[14]
2	Yoseph Barash	[6] [9]
3	Gal Chechik	[14]
4	David Cohen	[16]
5	John Duchi	[13]
6	Nir Friedman	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]
7	Stephen Gould	[16] [19]
8	Geremy Heitz	[14] [15] [17] [18] [20]
9	Ariel Jaimovich	[10] [11]
10	Tommy Kaplan	[6] [9]
11	Daphne Koller	[1] [12] [13] [14] [15] [16] [17] [18] [20]
12	Noam Lotner	[1]
13	Hanah Margalit	[10] [11]
14	Ian McGraw	[12]
15	Iftach Nachman	[7]
16	Matan Ninio	[4]
17	Benjamin Packer	[17] [18] [20]
18	Dana Pe'er	[3]
19	Aviv Regev	[3]
20	Jim Rodgers	[16]
21	Dale Shuurmans	[4]
22	Daniel Tarlow	[13]