Elidan, Gal

39 publications

ICLR 2025 Do LLMs Have Consistent Values? Naama Rozen, Liat Bezalel, Gal Elidan, Amir Globerson, Ella Daniel

NeurIPS 2024 TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools Avi Caciularu, Alon Jacovi, Eyal Ben-David, Sasha Goldshtein, Tal Schuster, Jonathan Herzig, Gal Elidan, Amir Globerson

UAI 2022 Active Learning with Label Comparisons Gal Yona, Shay Moran, Gal Elidan, Amir Globerson

ICCV 2021 Explaining in Style: Training a GAN to Explain a Classifier in StyleSpace Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri

ICLR 2021 Net-DNF: Effective Deep Modeling of Tabular Data Liran Katzir, Gal Elidan, Ran El-Yaniv

NeurIPS 2019 Globally Optimal Learning for Structured Elliptical Losses Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel

AISTATS 2019 Learning Rules-First Classifiers Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan

IJCAI 2017 Logistic Markov Decision Processes Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu

UAI 2017 Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, UAI 2017, Sydney, Australia, August 11-15, 2017 Gal Elidan, Kristian Kersting, Alexander Ihler

AISTATS 2017 Scalable Learning of Non-Decomposable Objectives Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan

AISTATS 2016 Generalized Ideal Parent (GIP): Discovering Non-Gaussian Hidden Variables Yaniv Tenzer, Gal Elidan

AISTATS 2016 Improper Deep Kernels Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson

UAI 2014 HELM: Highly Efficient Learning of Mixed Copula Networks Yaniv Tenzer, Gal Elidan

AISTATS 2013 Dynamic Copula Networks for Modeling Real-Valued Time Series Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan

UAI 2013 Learning Max-Margin Tree Predictors Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson

UAI 2013 Speedy Model Selection (SMS) for Copula Models Yaniv Tenzer, Gal Elidan

AISTATS 2012 Copula Network Classifiers (CNCs) Gal Elidan

AISTATS 2012 Lightning-Speed Structure Learning of Nonlinear Continuous Networks Gal Elidan

NeurIPS 2012 Nonparanormal Belief Propagation (NPNBP) Gal Elidan, Cobi Cario

AISTATS 2011 Bagged Structure Learning of Bayesian Network Gal Elidan

NeurIPS 2010 Copula Bayesian Networks Gal Elidan

MLOSS 2010 FastInf: An Efficient Approximate Inference Library Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan

UAI 2010 Inference-Less Density Estimation Using Copula Bayesian Networks Gal Elidan

UAI 2008 Convex Point Estimation Using Undirected Bayesian Transfer Hierarchies Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller

JMLR 2008 Learning Bounded Treewidth Bayesian Networks Gal Elidan, Stephen Gould

NeurIPS 2008 Learning Bounded Treewidth Bayesian Networks Gal Elidan, Stephen Gould

JMLR 2008 Max-Margin Classification of Data with Absent Features Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

NeurIPS 2008 Shape-Based Object Localization for Descriptive Classification Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller

JMLR 2007 "Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks Gal Elidan, Iftach Nachman, Nir Friedman

CVPR 2006 Learning Object Shape: From Drawings to Images Gal Elidan, Geremy Heitz, Daphne Koller

NeurIPS 2006 Max-Margin Classification of Incomplete Data Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

UAI 2006 Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing Gal Elidan, Ian McGraw, Daphne Koller

NeurIPS 2006 Using Combinatorial Optimization Within Max-Product Belief Propagation Daniel Tarlow, Gal Elidan, Daphne Koller, John C. Duchi

JMLR 2005 Learning Hidden Variable Networks: The Information Bottleneck Approach Gal Elidan, Nir Friedman

UAI 2004 "Ideal Parent" Structure Learning for Continuous Variable Networks Iftach Nachman, Gal Elidan, Nir Friedman

UAI 2003 The Information Bottleneck EM Algorithm Gal Elidan, Nir Friedman

AAAI 2002 Data Perturbation for Escaping Local Maxima in Learning Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans

UAI 2001 Learning the Dimensionality of Hidden Variables Gal Elidan, Nir Friedman

NeurIPS 2000 Discovering Hidden Variables: A Structure-Based Approach Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller