El-Yaniv, Ran

56 publications

TMLR 2026 Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips Ido Galil, Moshe Kimhi, Ran El-Yaniv

NeurIPS 2025 FFN Fusion: Rethinking Sequential Computation in Large Language Models Akhiad Bercovich, Mohammed Dabbah, Omri Puny, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Ehud Dov Karpas, Itay Levy, Zach Moshe, Najeeb Nabwani, Tomer Ronen, Itamar Schen, Ido Shahaf, Oren Tropp, Ran Zilberstein, Ran El-Yaniv

ICLRW 2025 Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron

ICML 2025 Puzzle: Distillation-Based NAS for Inference-Optimized LLMs Akhiad Bercovich, Tomer Ronen, Talor Abramovich, Nir Ailon, Nave Assaf, Mohammed Dabbah, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Netanel Haber, Ehud Dov Karpas, Roi Koren, Itay Levy, Pavlo Molchanov, Shahar Mor, Zach Moshe, Najeeb Nabwani, Omri Puny, Ran Rubin, Itamar Schen, Ido Shahaf, Oren Tropp, Omer Ullman Argov, Ran Zilberstein, Ran El-Yaniv

NeurIPS 2024 Hierarchical Selective Classification Shani Goren, Ido Galil, Ran El-Yaniv

ICLR 2023 A Framework for Benchmarking Class-Out-of-Distribution Detection and Its Application to ImageNet Ido Galil, Mohammed Dabbah, Ran El-Yaniv

ICLR 2023 What Can We Learn from the Selective Prediction and Uncertainty Estimation Performance of 523 ImageNet Classifiers? Ido Galil, Mohammed Dabbah, Ran El-Yaniv

NeurIPS 2023 Window-Based Distribution Shift Detection for Deep Neural Networks Guy Bar-Shalom, Yonatan Geifman, Ran El-Yaniv

NeurIPS 2022 TransBoost: Improving the Best ImageNet Performance Using Deep Transduction Omer Belhasin, Guy Bar-Shalom, Ran El-Yaniv

NeurIPS 2021 Disrupting Deep Uncertainty Estimation Without Harming Accuracy Ido Galil, Ran El-Yaniv

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

WACV 2021 TranstextNet: Transducing Text for Recognizing Unseen Visual Relationships Gal S. Kenigsfield, Ran El-Yaniv

AISTATS 2020 Long-and Short-Term Forecasting for Portfolio Selection with Transaction Costs Guy Uziel, Ran El-Yaniv

ICLR 2019 Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman, Guy Uziel, Ran El-Yaniv

NeurIPS 2019 Deep Active Learning with a Neural Architecture Search Yonatan Geifman, Ran El-Yaniv

ICML 2019 SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman, Ran El-Yaniv

JMLR 2019 The Relationship Between Agnostic Selective Classification, Active Learning and the Disagreement Coefficient Roei Gelbhart, Ran El-Yaniv

NeurIPS 2018 Deep Anomaly Detection Using Geometric Transformations Izhak Golan, Ran El-Yaniv

AISTATS 2018 Growth-Optimal Portfolio Selection Under CVaR Constraints Guy Uziel, Ran El-Yaniv

AAAI 2018 Toward Deep Reinforcement Learning Without a Simulator: An Autonomous Steering Example Bar Hilleli, Ran El-Yaniv

NeurIPS 2017 Multi-Objective Non-Parametric Sequential Prediction Guy Uziel, Ran El-Yaniv

NeurIPS 2017 Selective Classification for Deep Neural Networks Yonatan Geifman, Ran El-Yaniv

NeurIPS 2016 Binarized Neural Networks Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

JMLR 2015 A Compression Technique for Analyzing Disagreement-Based Active Learning Yair Wiener, Steve Hanneke, Ran El-Yaniv

JAIR 2015 Agnostic Pointwise-Competitive Selective Classification Yair Wiener, Ran El-Yaniv

ICML 2014 Concept Drift Detection Through Resampling Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer

JMLR 2012 Active Learning via Perfect Selective Classification Ran El-Yaniv, Yair Wiener

NeurIPS 2012 Pointwise Tracking the Optimal Regression Function Yair Wiener, Ran El-Yaniv

ECML-PKDD 2012 Supervised Learning of Semantic Relatedness Ran El-Yaniv, David Yanay

NeurIPS 2011 Agnostic Selective Classification Yair Wiener, Ran El-Yaniv

NeurIPS 2011 Selective Prediction of Financial Trends with Hidden Markov Models Dmitry Pidan, Ran El-Yaniv

JMLR 2010 On the Foundations of Noise-Free Selective Classification Ran El-Yaniv, Yair Wiener

JAIR 2009 Transductive Rademacher Complexity and Its Applications Ran El-Yaniv, Dmitry Pechyony

ECML-PKDD 2008 Large Margin vs. Large Volume in Transductive Learning Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik

MLJ 2008 Large Margin vs. Large Volume in Transductive Learning Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik

COLT 2007 Transductive Rademacher Complexity and Its Applications Ran El-Yaniv, Dmitry Pechyony

NeurIPS 2006 Optimal Single-Class Classification Strategies Ran El-Yaniv, Mordechai Nisenson

COLT 2006 Stable Transductive Learning Ran El-Yaniv, Dmitry Pechyony

JMLR 2006 Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition Ron Begleiter, Ran El-Yaniv

ICML 2005 Multi-Way Distributional Clustering via Pairwise Interactions Ron Bekkerman, Ran El-Yaniv, Andrew McCallum

JAIR 2004 Can We Learn to Beat the Best Stock Allan Borodin, Ran El-Yaniv, Vincent Gogan

JAIR 2004 Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms Philip Derbeko, Ran El-Yaniv, Ron Meir

MLJ 2004 How to Better Use Expert Advice Rani Yaroshinsky, Ran El-Yaniv, Steven S. Seiden

JAIR 2004 On Prediction Using Variable Order Markov Models Ron Begleiter, Ran El-Yaniv, Golan Yona

JMLR 2004 Online Choice of Active Learning Algorithms Yoram Baram, Ran El Yaniv, Kobi Luz

NeurIPS 2003 Can We Learn to Beat the Best Stock Allan Borodin, Ran El-Yaniv, Vincent Gogan

NeurIPS 2003 Error Bounds for Transductive Learning via Compression and Clustering Philip Derbeko, Ran El-Yaniv, Ron Meir

ICML 2003 Online Choice of Active Learning Algorithms Yoram Baram, Ran El-Yaniv, Kobi Luz

MLJ 2002 A New Nonparametric Pairwise Clustering Algorithm Based on Iterative Estimation of Distance Profiles Shlomo Dubnov, Ran El-Yaniv, Yoram Gdalyahu, Elad Schneidman, Naftali Tishby, Golan Yona

JMLR 2002 On Online Learning of Decision Lists Ziv Nevo, Ran El-Yaniv

ECML-PKDD 2002 Variance Optimized Bagging Philip Derbeko, Ran El-Yaniv, Ron Meir

NeurIPS 2001 Iterative Double Clustering for Unsupervised and Semi-Supervised Learning Ran El-Yaniv, Oren Souroujon

ECML-PKDD 2001 Iterative Double Clustering for Unsupervised and Semi-Supervised Learning Ran El-Yaniv, Oren Souroujon

ICML 2001 Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation Gregory Shakhnarovich, Ran El-Yaniv, Yoram Baram

COLT 2000 Localized Boosting Ron Meir, Ran El-Yaniv, Shai Ben-David

NeurIPS 1997 Agnostic Classification of Markovian Sequences Ran El-Yaniv, Shai Fine, Naftali Tishby