Gal Elidan

According to our database, Gal Elidan authored at least 66 papers between 2000 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback.

Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment.

Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning.

Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan

CoRR, 2022

Active learning with label comparisons.

Gal Yona, Shay Moran, Gal Elidan, Amir Globerson

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Convex Nonparanormal Regression.

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

IEEE Signal Process. Lett., 2021

Flood forecasting with machine learning models in an operational framework.

Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, Yossi Matias

CoRR, 2021

Solving Sokoban with Forward-Backward Reinforcement Learning.

Yaron Shoham, Gal Elidan

Proceedings of the Fourteenth International Symposium on Combinatorial Search, 2021

Net-DNF: Effective Deep Modeling of Tabular Data.

Liran Katzir, Gal Elidan, Ran El-Yaniv

Proceedings of the 9th International Conference on Learning Representations, 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

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach.

Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev, Oren Gilon, Grey Nearing, Yossi Matias

CoRR, 2020

HydroNets: Leveraging River Structure for Hydrologic Modeling.

Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv

CoRR, 2020

DNF-Net: A Neural Architecture for Tabular Data.

Ami Abutbul, Gal Elidan, Liran Katzir, Ran El-Yaniv

CoRR, 2020

Normalizing Flow Regression.

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

CoRR, 2020

Dynamic Composition for Conversational Domain Exploration.

Idan Szpektor, Deborah Cohen, Gal Elidan, Michael Fink, Avinatan Hassidim, Orgad Keller, Sayali Kulkarni, Eran Ofek, Sagie Pudinsky, Asaf Revach, Shimi Salant, Yossi Matias

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Spectral Algorithm for Shared Low-rank Matrix Regressions.

Yotam Gigi, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias, Ami Wiesel

Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020

2019

Unmixing K-Gaussians With Application to Hyperspectral Imaging.

Yonatan Woodbridge, Uri Okun, Gal Elidan, Ami Wiesel

IEEE Trans. Geosci. Remote. Sens., 2019

Improved Detection of Adversarial Attacks via Penetration Distortion Maximization.

Shai Rozenberg, Gal Elidan, Ran El-Yaniv

CoRR, 2019

Spectral Algorithm for Low-rank Multitask Regression.

Yotam Gigi, Ami Wiesel, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias

CoRR, 2019

ML for Flood Forecasting at Scale.

Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias

CoRR, 2019

Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many.

Yotam Gigi, Gal Elidan, Avinatan Hassidim, Yossi Matias, Zach Moshe, Sella Nevo, Guy Shalev, Ami Wiesel

CoRR, 2019

Globally Optimal Learning for Structured Elliptical Losses.

Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robust multitask Elliptical Regression (ROMER).

Nofar Noy, Yoav Wald, Gal Elidan, Ami Wiesel

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Learning Rules-First Classifiers.

Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning with Rules.

Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan

CoRR, 2018

2017

Signal Detection in Complex Structured Para Normal Noise.

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

IEEE Trans. Signal Process., 2017

Logistic Markov Decision Processes.

Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Scalable Learning of Non-Decomposable Objectives.

Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Large-scale Learning With Global Non-Decomposable Objectives.

Elad Eban, Mariano Schain, Ariel Gordon, Rif Saurous, Gal Elidan

CoRR, 2016

Signal detection in para complex normal noise.

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables.

Yaniv Tenzer, Gal Elidan

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Improper Deep Kernels.

Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Quaternion structured paranormal distributions.

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2014

HELM: Highly Efficient Learning of Mixed copula networks.

Yaniv Tenzer, Gal Elidan

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

2013

Speedy Model Selection (SMS) for Copula Models.

Yaniv Tenzer, Gal Elidan

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Learning Max-Margin Tree Predictors.

Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Dynamic Copula Networks for Modeling Real-valued Time Series.

Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Lightning-speed Structure Learning of Nonlinear Continuous Networks.

Gal Elidan

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Copula Network Classifiers (CNCs).

Gal Elidan

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Nonparanormal Belief Propagation (NPNBP).

Gal Elidan, Cobi Cario

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Diverse Dirichlet Process Ensemble for Unsupervised Induction of Syntactic Categories.

Roi Reichart, Gal Elidan, Ari Rappoport

Proceedings of the COLING 2012, 2012

2011

Bagged Structure Learning of Bayesian Network.

Gal Elidan

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010

FastInf: An Efficient Approximate Inference Library.

Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan

J. Mach. Learn. Res., 2010

Inference-less Density Estimation using Copula Bayesian Networks.

Gal Elidan

Proceedings of the UAI 2010, 2010

Copula Bayesian Networks.

Gal Elidan

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Shape-Based Object Localization for Descriptive Classification.

Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller

Int. J. Comput. Vis., 2009

2008

Max-margin Classification of Data with Absent Features.

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

J. Mach. Learn. Res., 2008

Multi-Class Segmentation with Relative Location Prior.

Stephen Gould, Jim Rodgers, David Cohen, Gal Elidan, Daphne Koller

Int. J. Comput. Vis., 2008

Convex Point Estimation using Undirected Bayesian Transfer Hierarchies.

Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller

Proceedings of the UAI 2008, 2008

Learning Bounded Treewidth Bayesian Networks.

Gal Elidan, Stephen Gould

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks.

Gal Elidan, Iftach Nachman, Nir Friedman

J. Mach. Learn. Res., 2007

2006

Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach.

Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman

J. Comput. Biol., 2006

Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing.

Gal Elidan, Ian McGraw, Daphne Koller

Proceedings of the UAI '06, 2006

Using Combinatorial Optimization within Max-Product Belief Propagation.

John C. Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Max-margin classification of incomplete data.

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Learning Object Shape: From Drawings to Images.

Gal Elidan, Geremy Heitz, Daphne Koller

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

2005

Learning Hidden Variable Networks: The Information Bottleneck Approach.

Gal Elidan, Nir Friedman

J. Mach. Learn. Res., 2005

CIS: compound importance sampling method for protein-DNA binding site p-value estimation.

Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman

Bioinform., 2005

Towards an Integrated Protein-Protein Interaction Network.

Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman

Proceedings of the Research in Computational Molecular Biology, 2005

2004

Learning hidden variables in probabilistic graphical models (למידת משתנים חבויים במודלים גרפיים הסתברותיים.).

Gal Elidan

PhD thesis, 2004

"Ideal Parent" Structure Learning for Continuous Variable Networks.

Iftach Nachman, Gal Elidan, Nir Friedman

Proceedings of the UAI '04, 2004

2003

The Information Bottleneck EM Algorithm.

Gal Elidan, Nir Friedman

Proceedings of the UAI '03, 2003

Modeling dependencies in protein-DNA binding sites.

Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan

Proceedings of the Sventh Annual International Conference on Computational Biology, 2003

2002

Data Perturbation for Escaping Local Maxima in Learning.

Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans

Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001

Learning the Dimensionality of Hidden Variables.

Gal Elidan, Nir Friedman

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Inferring subnetworks from perturbed expression profiles.

Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman

Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001

2000

Discovering Hidden Variables: A Structure-Based Approach.

Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller

Proceedings of the Advances in Neural Information Processing Systems 13, 2000