Gal Elidan
Cited by
Cited by
Inferring subnetworks from perturbed expression profiles
D Pe’er, A Regev, G Elidan, N Friedman
Bioinformatics 17 (suppl_1), S215-S224, 2001
Multi-class segmentation with relative location prior
S Gould, J Rodgers, D Cohen, G Elidan, D Koller
International journal of computer vision 80 (3), 300-316, 2008
Residual belief propagation: Informed scheduling for asynchronous message passing
G Elidan, I McGraw, D Koller
arXiv preprint arXiv:1206.6837, 2012
Modeling dependencies in protein-DNA binding sites
Y Barash, G Elidan, N Friedman, T Kaplan
Proceedings of the seventh annual international conference on Research in …, 2003
Discovering hidden variables: A structure-based approach
G Elidan, N Lotner, N Friedman, D Koller
NIPS 13, 479-485, 2000
Markov random field based automatic image alignment for electron tomography
F Amat, F Moussavi, LR Comolli, G Elidan, KH Downing, M Horowitz
Journal of structural biology 161 (3), 260-275, 2008
Max-margin classification of data with absent features
G Chechik, G Heitz, G Elidan, P Abbeel, D Koller
The Journal of Machine Learning Research 9, 1-21, 2008
Max-margin Classification of Data with Absent Features.
G Chechik, G Heitz, G Elidan, P Abbeel, D Koller
Journal of Machine Learning Research 9 (1), 2008
Copula Bayesian Networks.
G Elidan
NIPS, 559-567, 2010
Learning Hidden Variable Networks: The Information Bottleneck Approach.
G Elidan, N Friedman, DM Chickering
Journal of Machine Learning Research 6 (1), 2005
Data perturbation for escaping local maxima in learning
G Elidan, M Ninio, N Friedman, D Schuurmans
AAAI/IAAI, 132-139, 2002
Using combinatorial optimization within max-product belief propagation
J Elidan, D Koller
Advances in neural information processing systems 19, 369, 2007
Learning the dimensionality of hidden variables
G Elidan, N Friedman
arXiv preprint arXiv:1301.2269, 2013
Learning Bounded Treewidth Bayesian Networks.
G Elidan, S Gould
Journal of Machine Learning Research 9 (12), 2008
Towards an integrated protein–protein interaction network: A relational Markov network approach
A Jaimovich, G Elidan, H Margalit, N Friedman
Journal of Computational Biology 13 (2), 145-164, 2006
Scalable learning of non-decomposable objectives
E Eban, M Schain, A Mackey, A Gordon, R Rifkin, G Elidan
Artificial intelligence and statistics, 832-840, 2017
Copulas in machine learning
G Elidan
Copulae in mathematical and quantitative finance, 39-60, 2013
Shape-based object localization for descriptive classification
G Heitz, G Elidan, B Packer, D Koller
International journal of computer vision 84 (1), 40-62, 2009
" Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks.
G Elidan, I Nachman, N Friedman
Journal of Machine Learning Research 8 (8), 2007
Learning object shape: From drawings to images
G Elidan, G Heitz, D Koller
2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006
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