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Gal Elidan

29 papers · 2005–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (20) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (13) 🌍 Conference Polyglot (9) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (9) 🧭 Keyword Pioneer 🐺 Lone Wolf (4) 🌟 Keyword Trendsetter Combo (9) πŸ† Keyword Champion 🧬 Topic Evolution πŸ’Ž Century Club (29) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (57) ❓ The Questioner πŸ”₯ Unstoppable (5)

Conferences

AISTATS (8) NIPS (8) JMLR (5) ACL (2) ICLR (2) COLING (1) ICCV (1) IJCAI (1) UAI (1)

Top co-authors

Amir Globerson (7) Daphne Koller (4) Geremy Heitz (3) Elad Eban (3) Stephen Gould (2) Yoav Wald (2) Pieter Abbeel (2) Avinatan Hassidim (2) Nir Friedman (2) Gal Chechik (2)

Research topics

Education (1)

Keywords

graphical model (9) bayesian network (9) structure learning (4) belief propagation (3) probabilistic graphical model (3) probabilistic modeling (3) support vector machine (3) sample complexity (3) hidden variable (3) copula network (2) variational inference (2) approximate inference (2) feature learning (2) multivariate distribution (2) gaussian copula (2) probabilistic inference (2) max-margin classification (2) missing feature (2) structured prediction (1) convex optimization (1)

Papers

Do LLMs have Consistent Values? ICLR 2025
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools NIPS 2024
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback ACL 2023
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment ACL 2023
Active learning with label comparisons UAI 2022
Net-DNF: Effective Deep Modeling of Tabular Data ICLR 2021
Explaining in Style: Training a GAN To Explain a Classifier in StyleSpace ICCV 2021
Learning Rules-First Classifiers AISTATS 2019
Globally Optimal Learning for Structured Elliptical Losses NIPS 2019
Logistic Markov Decision Processes IJCAI 2017
Scalable Learning of Non-Decomposable Objectives AISTATS 2017
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables AISTATS 2016
Improper Deep Kernels AISTATS 2016
Dynamic Copula Networks for Modeling Real-valued Time Series AISTATS 2013
Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012
Copula Network Classifiers (CNCs) AISTATS 2012
A Diverse Dirichlet Process Ensemble for Unsupervised Induction of Syntactic Categories COLING 2012
Nonparanormal Belief Propagation (NPNBP) NIPS 2012
Bagged Structure Learning of Bayesian Network AISTATS 2011
Copula Bayesian Networks NIPS 2010
FastInf: An Efficient Approximate Inference Library JMLR 2010
Shape-Based Object Localization for Descriptive Classification NIPS 2008
Learning Bounded Treewidth Bayesian Networks NIPS 2008
Max-margin Classification of Data with Absent Features JMLR 2008
Learning Bounded Treewidth Bayesian Networks JMLR 2008
"Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks JMLR 2007
Using Combinatorial Optimization within Max-Product Belief Propagation NIPS 2006
Max-margin classification of incomplete data NIPS 2006
Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005