Gilad-Bachrach, Ran

22 publications

NeurIPS 2025 Depth-Width Tradeoffs for Transformers on Graph Tasks Gilad Yehudai, Clayton Sanford, Maya Bechler-Speicher, Orr Fischer, Ran Gilad-Bachrach, Amir Globerson

ICML 2024 Graph Neural Networks Use Graphs When They Shouldn’t Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

AAAI 2024 TREE-G: Decision Trees Contesting Graph Neural Networks Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

NeurIPS 2024 The Intelligible and Effective Graph Neural Additive Network Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

NeurIPSW 2023 A Work in Progress: Tighter Bounds on the Information Bottleneck for Deep Learning Nir Weingarten, Moshe Butman, Ran Gilad-Bachrach

NeurIPSW 2023 Inherent Inconsistencies of Feature Importance Nimrod Harel, Uri Obolski, Ran Gilad-Bachrach

AISTATS 2022 A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach

ICML 2021 Marginal Contribution Feature Importance - An Axiomatic Approach for Explaining Data Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

AAAI 2021 Robust Model Compression Using Deep Hypotheses Omri Armstrong, Ran Gilad-Bachrach

ICML 2021 Trees with Attention for Set Prediction Tasks Roy Hirsch, Ran Gilad-Bachrach

ICML 2019 Low Latency Privacy Preserving Inference Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha

ICML 2016 CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, John Wernsing

AISTATS 2015 DART: Dropouts Meet Multiple Additive Regression Trees Korlakai Vinayak Rashmi, Ran Gilad-Bachrach

JMLR 2013 Classifier Selection Using the Predicate Depth Ran Gilad-Bachrach, Christopher J.C. Burges

NeurIPS 2013 Using Multiple Samples to Learn Mixture Models Jason Lee, Ran Gilad-Bachrach, Rich Caruana

JMLR 2012 Optimal Distributed Online Prediction Using Mini-Batches Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao

ICML 2011 Optimal Distributed Online Prediction Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao

NeurIPS 2005 Query by Committee Made Real Ran Gilad-bachrach, Amir Navot, Naftali Tishby

COLT 2004 Bayes and Tukey Meet at the Center Point Ran Gilad-Bachrach, Amir Navot, Naftali Tishby

ICML 2004 Margin Based Feature Selection - Theory and Algorithms Ran Gilad-Bachrach, Amir Navot, Naftali Tishby

COLT 2003 An Information Theoretic Tradeoff Between Complexity and Accuracy Ran Gilad-Bachrach, Amir Navot, Naftali Tishby

NeurIPS 2002 Margin Analysis of the LVQ Algorithm Koby Crammer, Ran Gilad-bachrach, Amir Navot, Naftali Tishby