Blum, Avrim

93 publications

ALT 2025 A Model for Combinatorial Dictionary Learning and Inference Avrim Blum, Kavya Ravichandran

AISTATS 2025 Distributional Adversarial Loss Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain

TMLR 2025 Learning Actionable Counterfactual Explanations in Large State Spaces Keziah Naggita, Matthew Walter, Avrim Blum

ALT 2025 Nearly-Tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem Avrim Blum, Kavya Ravichandran

NeurIPS 2025 On Learning Verifiers and Implications to Chain-of-Thought Reasoning Maria Florina Balcan, Avrim Blum, Zhiyuan Li, Dravyansh Sharma

ICML 2025 PAC Learning with Improvements Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew Walter

COLT 2025 Proofs as Explanations: Short Certificates for Reliable Predictions Avrim Blum, Steve Hanneke, Chirag Pabbaraju, Donya Saless

NeurIPS 2025 Replicable Online Learning Saba Ahmadi, Siddharth Bhandari, Avrim Blum

AISTATS 2024 Agnostic Multi-Robust Learning Using ERM Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M Stangl

ALT 2024 Dueling Optimization with a Monotone Adversary Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang

AISTATS 2024 On the Vulnerability of Fairness Constrained Learning to Malicious Noise Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin M. Stangl

JMLR 2023 An Analysis of Robustness of Non-Lipschitz Networks Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang

NeurIPSW 2023 Dueling Optimization with a Monotone Adversary Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang

NeurIPS 2023 Eliciting User Preferences for Personalized Multi-Objective Decision Making Through Comparative Feedback Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter

NeurIPS 2023 Strategic Classification Under Unknown Personalized Manipulation Han Shao, Avrim Blum, Omar Montasser

NeurIPS 2022 A Theory of PAC Learnability Under Transformation Invariances Han Shao, Omar Montasser, Avrim Blum

NeurIPS 2022 Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang

NeurIPSW 2022 Certifiable Robustness Against Patch Attacks Using an ERM Oracle Kevin Stangl, Avrim Blum, Omar Montasser, Saba Ahmadi

COLT 2022 Robustly-Reliable Learners Under Poisoning Attacks Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma

AISTATS 2021 Learning Complexity of Simulated Annealing Avrim Blum, Chen Dan, Saeed Seddighin

AAAI 2021 Communication-Aware Collaborative Learning Avrim Blum, Shelby Heinecke, Lev Reyzin

NeurIPS 2021 Excess Capacity and Backdoor Poisoning Naren Manoj, Avrim Blum

ICML 2021 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao

COLT 2021 Robust Learning Under Clean-Label Attack Avrim Blum, Steve Hanneke, Jian Qian, Han Shao

COLT 2020 Active Local Learning Arturs Backurs, Avrim Blum, Neha Gupta

NeurIPS 2020 Online Learning with Primary and Secondary Losses Avrim Blum, Han Shao

JMLR 2020 Random Smoothing Might Be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang

COLT 2018 Active Tolerant Testing Avrim Blum, Lunjia Hu

AAAI 2018 Algorithms for Generalized Topic Modeling Avrim Blum, Nika Haghtalab

NeurIPS 2018 On Preserving Non-Discrimination When Combining Expert Advice Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nati Srebro

NeurIPS 2017 Collaborative PAC Learning Avrim Blum, Nika Haghtalab, Ariel D Procaccia, Mingda Qiao

COLT 2017 Efficient Co-Training of Linear Separators Under Weak Dependence Avrim Blum, Yishay Mansour

COLT 2017 Efficient PAC Learning from the Crowd Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour

ALT 2017 Lifelong Learning in Costly Feature Spaces Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan

COLT 2015 Efficient Representations for Lifelong Learning and Autoencoding Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala

AAAI 2015 Learning Valuation Distributions from Partial Observation Avrim Blum, Yishay Mansour, Jamie Morgenstern

ICML 2015 The Ladder: A Reliable Leaderboard for Machine Learning Competitions Avrim Blum, Moritz Hardt

NeurIPS 2014 Active Learning and Best-Response Dynamics Maria-Florina F Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song

UAI 2014 Estimating Accuracy from Unlabeled Data Emmanouil Antonios Platanios, Avrim Blum, Tom M. Mitchell

AAAI 2014 Lazy Defenders Are Almost Optimal Against Diligent Attackers Avrim Blum, Nika Haghtalab, Ariel D. Procaccia

NeurIPS 2014 Learning Mixtures of Ranking Models Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan

NeurIPS 2014 Learning Optimal Commitment to Overcome Insecurity Avrim Blum, Nika Haghtalab, Ariel D Procaccia

ICML 2013 Exploiting Ontology Structures and Unlabeled Data for Learning Nina Balcan, Avrim Blum, Yishay Mansour

COLT 2012 Distributed Learning, Communication Complexity and Privacy Maria Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour

COLT 2010 Improved Guarantees for Agnostic Learning of Disjunctions Pranjal Awasthi, Avrim Blum, Or Sheffet

NeurIPS 2010 Trading Off Mistakes and Don't-Know Predictions Amin Sayedi, Morteza Zadimoghaddam, Avrim Blum

NeurIPS 2009 Tracking Dynamic Sources of Malicious Activity at Internet Scale Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck

MLJ 2008 A Theory of Learning with Similarity Functions Maria-Florina Balcan, Avrim Blum, Nathan Srebro

ALT 2008 Clustering with Interactive Feedback Maria-Florina Balcan, Avrim Blum

COLT 2008 Improved Guarantees for Learning via Similarity Functions Maria-Florina Balcan, Avrim Blum, Nathan Srebro

ALT 2007 A Theory of Similarity Functions for Learning and Clustering Avrim Blum

JMLR 2007 From External to Internal Regret Avrim Blum, Yishay Mansour

MLJ 2007 Introduction to the Special Issue on COLT 2006 Avrim Blum, Gábor Lugosi, Hans Ulrich Simon

COLT 2007 Open Problems in Efficient Semi-Supervised PAC Learning Avrim Blum, Maria-Florina Balcan

MLJ 2006 Kernels as Features: On Kernels, Margins, and Low-Dimensional Mappings Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala

ICML 2006 On a Theory of Learning with Similarity Functions Maria-Florina Balcan, Avrim Blum

COLT 2005 A PAC-Style Model for Learning from Labeled and Unlabeled Data Maria-Florina Balcan, Avrim Blum

COLT 2005 From External to Internal Regret Avrim Blum, Yishay Mansour

NeurIPS 2004 Co-Training and Expansion: Towards Bridging Theory and Practice Maria-florina Balcan, Avrim Blum, Ke Yang

MLJ 2004 Correlation Clustering Nikhil Bansal, Avrim Blum, Shuchi Chawla

ALT 2004 On Kernels, Margins, and Low-Dimensional Mappings Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala

COLT 2004 Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary H. Brendan McMahan, Avrim Blum

JMLR 2004 Preference Elicitation and Query Learning (Special Topic on Learning Theory) Avrim Blum, Jeffrey Jackson, Tuomas Sandholm, Martin Zinkevich

ICML 2004 Semi-Supervised Learning Using Randomized Mincuts Avrim Blum, John D. Lafferty, Mugizi Robert Rwebangira, Rajashekar Reddy

COLT 2003 Learning a Function of R Relevant Variables Avrim Blum

MLJ 2003 Microchoice Bounds and Self Bounding Learning Algorithms John Langford, Avrim Blum

COLT 2003 PAC-MDL Bounds Avrim Blum, John Langford

ICML 2003 Planning in the Presence of Cost Functions Controlled by an Adversary H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum

COLT 2003 Preference Elicitation and Query Learning Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich

ICML 2001 Learning from Labeled and Unlabeled Data Using Graph Mincuts Avrim Blum, Shuchi Chawla

ICML 2000 FeatureBoost: A Meta-Learning Algorithm That Improves Model Robustness Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum

MLJ 2000 On-Line Learning and the Metrical Task System Problem Avrim Blum, Carl Burch

COLT 1999 Beating the Hold-Out: Bounds for K-Fold and Progressive Cross-Validation Avrim Blum, Adam Kalai, John Langford

COLT 1999 Microchoice Bounds and Self Bounding Learning Algorithms John Langford, Avrim Blum

MLJ 1999 Universal Portfolios with and Without Transaction Costs Avrim Blum, Adam Kalai

MLJ 1998 A Note on Learning from Multiple-Instance Examples Avrim Blum, Adam Kalai

COLT 1998 Combining Labeled and Unlabeled Data with Co-Training Avrim Blum, Tom M. Mitchell

MLJ 1997 Empirical Support for Winnow and Weighted-Majority Algorithms: Results on a Calendar Scheduling Domain Avrim Blum

COLT 1997 On-Line Learning and the Metrical Task System Problem Avrim Blum, Carl Burch

COLT 1997 Universal Portfolios with and Without Transaction Costs Avrim Blum, Adam Kalai

COLT 1996 Proceedings of the Ninth Annual Conference on Computational Learning Theory, COLT 1996, Desenzano Del Garda, Italy, June 28-July 1, 1996 Avrim Blum, Michael J. Kearns

ICML 1995 Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain Avrim Blum

IJCAI 1995 Fast Planning Through Planning Graph Analysis Avrim Blum, Merrick L. Furst

COLT 1995 Learning with Unreliable Boundary Queries Avrim Blum, Prasad Chalasani, Sally A. Goldman, Donna K. Slonim

COLT 1994 On Learning Read-K-Satisfy-J DNF Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth

COLT 1993 On Learning Embedded Symmetric Concepts Avrim Blum, Prasad Chalasani, Jeffrey C. Jackson

MLJ 1992 Learning Boolean Functions in an Infinite Attribute Space Avrim Blum

COLT 1992 Learning Switching Concepts Avrim Blum, Prasad Chalasani

COLT 1991 Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes Avrim Blum, Lisa Hellerstein, Nick Littlestone

COLT 1990 Learning Functions of K Terms Avrim Blum, Mona Singh

COLT 1990 Separating PAC and Mistake-Bound Learning Models over the Boolean Domain (Abstract) Avrim Blum

NeurIPS 1988 Training a 3-Node Neural Network Is NP-Complete Avrim Blum, Ronald L. Rivest

COLT 1988 Training a 3-Node Neural Network Is NP-Complete Avrim Blum, Ronald L. Rivest