Avrim Blum - RankMe

323 papers A* 119A 19B 14Misc 2Journal 141Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Theoretical Model for Grit in Pursuing Ambitious Ends. AAAI Avrim Blum, Emily Diana, Kavya Ravichandran, Alexander Williams Tolbert
2026	J	`jnl`	Online Learnability of Chain-of-Thought Verifiers: Soundness and Completeness Trade-offs. CoRR Maria-Florina Balcan, Avrim Blum, Kiriaki Fragkia, Zhiyuan Li, Dravyansh Sharma
2026	J	`jnl`	Revealing Positive and Negative Role Models to Help People Make Good Decisions. CoRR Avrim Blum, Keziah Naggita, Matthew R. Walter, Jingyan Wang
2025	J	`jnl`	A Machine Learning Theory Perspective on Strategic Litigation. CoRR Melissa Dutz, Han Shao, Avrim Blum, Aloni Cohen
2025	B	`conf`	A Model for Combinatorial Dictionary Learning and Inference. ALT Avrim Blum, Kavya Ravichandran
2025	J	`jnl`	A Theoretical Model for Grit in Pursuing Ambitious Ends. CoRR Avrim Blum, Emily Diana, Kavya Ravichandran, Alexander Williams Tolbert
2025	J	`jnl`	Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem. CoRR Avrim Blum, Marten Garicano, Kavya Ravichandran, Dravyansh Sharma
2025	A*	`conf`	Competitive strategies to use "warm start" algorithms with predictions. SODA Avrim Blum, Vaidehi Srinivas
2025	A	`conf`	Distributional Adversarial Loss. AISTATS Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain
2025	J	`jnl`	Learning Actionable Counterfactual Explanations in Large State Spaces. Trans. Mach. Learn. Res. Keziah Naggita, Matthew R. Walter, Avrim Blum
2025	B	`conf`	Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem. ALT Avrim Blum, Kavya Ravichandran
2025	J	`jnl`	On Learning Verifiers for Chain-of-Thought Reasoning. CoRR Maria-Florina Balcan, Avrim Blum, Zhiyuan Li, Dravyansh Sharma
2025	A*	`conf`	PAC Learning with Improvements. ICML Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025	J	`jnl`	PAC Learning with Improvements. CoRR Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025	—	`conf`	Pessimism Traps and Algorithmic Interventions. FORC Avrim Blum, Emily Diana, Kavya Ravichandran, Alexander Tolbert
2025	J	`jnl`	Prior Makes It Possible: From Sublinear Graph Algorithms to LLM Test-Time Methods. CoRR Avrim Blum, Daniel Hsu, Cyrus Rashtchian, Donya Saless
2025	A*	`conf`	Proofs as Explanations: Short Certificates for Reliable Predictions. COLT Avrim Blum, Steve Hanneke, Chirag Pabbaraju, Donya Saless
2025	J	`jnl`	Proofs as Explanations: Short Certificates for Reliable Predictions. CoRR Avrim Blum, Steve Hanneke, Chirag Pabbaraju, Donya Saless
2025	J	`jnl`	Strategic Filtering for Content Moderation: Free Speech or Free of Distortion? CoRR Saba Ahmadi, Avrim Blum, Haifeng Xu, Fan Yao
2024	J	`jnl`	A Model for Combinatorial Dictionary Learning and Inference. CoRR Avrim Blum, Kavya Ravichandran
2024	J	`jnl`	Adaptive Algorithmic Interventions for Escaping Pessimism Traps in Dynamic Sequential Decisions. CoRR Emily Diana, Alexander Williams Tolbert, Kavya Ravichandran, Avrim Blum
2024	A	`conf`	Agnostic Multi-Robust Learning using ERM. AISTATS Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M. Stangl
2024	J	`jnl`	Competitive strategies to use "warm start" algorithms with predictions. CoRR Vaidehi Srinivas, Avrim Blum
2024	J	`jnl`	Distributional Adversarial Loss. CoRR Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain
2024	B	`conf`	Dueling Optimization with a Monotone Adversary. ALT Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang
2024	J	`jnl`	Learning Actionable Counterfactual Explanations in Large State Spaces. CoRR Keziah Naggita, Matthew R. Walter, Avrim Blum
2024	J	`jnl`	Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem. CoRR Avrim Blum, Kavya Ravichandran
2024	A	`conf`	On the Vulnerability of Fairness Constrained Learning to Malicious Noise. AISTATS Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin M. Stangl
2024	J	`jnl`	Regularized Robustly Reliable Learners and Instance Targeted Attacks. CoRR Avrim Blum, Donya Saless
2024	J	`jnl`	Replicable Online Learning. CoRR Saba Ahmadi, Siddharth Bhandari, Avrim Blum
2024	A	`conf`	Winning Without Observing Payoffs: Exploiting Behavioral Biases to Win Nearly Every Round. ITCS Avrim Blum, Melissa Dutz
2024	J	`jnl`	Winning Without Observing Payoffs: Exploiting Behavioral Biases to Win Nearly Every Round. CoRR Avrim Blum, Melissa Dutz
2023	J	`jnl`	An Analysis of Robustness of Non-Lipschitz Networks. J. Mach. Learn. Res. Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
2023	J	`jnl`	Certifiable (Multi)Robustness Against Patch Attacks Using ERM. CoRR Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin Stangl
2023	J	`jnl`	Dueling Optimization with a Monotone Adversary. CoRR Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang
2023	A*	`conf`	Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. NeurIPS Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter
2023	J	`jnl`	Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. CoRR Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter
2023	A*	`conf`	Fundamental Bounds on Online Strategic Classification. EC Saba Ahmadi, Avrim Blum, Kunhe Yang
2023	J	`jnl`	Fundamental Bounds on Online Strategic Classification. CoRR Saba Ahmadi, Avrim Blum, Kunhe Yang
2023	J	`jnl`	On the Vulnerability of Fairness Constrained Learning to Malicious Noise. CoRR Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin Stangl
2023	—	`conf`	Setting Fair Incentives to Maximize Improvement. FORC Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2023	A*	`conf`	Strategic Classification under Unknown Personalized Manipulation. NeurIPS Han Shao, Avrim Blum, Omar Montasser
2023	J	`jnl`	Strategic Classification under Unknown Personalized Manipulation. CoRR Han Shao, Avrim Blum, Omar Montasser
2022	A*	`conf`	A Theory of PAC Learnability under Transformation Invariances. NeurIPS Han Shao, Omar Montasser, Avrim Blum
2022	J	`jnl`	A Theory of PAC Learnability under Transformation Invariances. CoRR Han Shao, Omar Montasser, Avrim Blum
2022	A*	`conf`	Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. NeurIPS Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
2022	J	`jnl`	Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. CoRR Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
2022	—	`conf`	Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. FAccT Avrim Blum, Kevin Stangl, Ali Vakilian
2022	J	`jnl`	Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. CoRR Avrim Blum, Kevin Stangl, Ali Vakilian
2022	—	`conf`	On Classification of Strategic Agents Who Can Both Game and Improve. FORC Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2022	J	`jnl`	On classification of strategic agents who can both game and improve. CoRR Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2022	A*	`conf`	Robustly-reliable learners under poisoning attacks. COLT Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
2022	J	`jnl`	Robustly-reliable learners under poisoning attacks. CoRR Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
2022	J	`jnl`	Setting Fair Incentives to Maximize Improvement. CoRR Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2022	A*	`conf`	Stochastic Vertex Cover with Few Queries. SODA Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan
2021	A*	`conf`	Communication-Aware Collaborative Learning. AAAI Avrim Blum, Shelby Heinecke, Lev Reyzin
2021	A*	`conf`	Excess Capacity and Backdoor Poisoning. NeurIPS Naren Manoj, Avrim Blum
2021	J	`jnl`	Excess Capacity and Backdoor Poisoning. CoRR Naren Sarayu Manoj, Avrim Blum
2021	A*	`conf`	Incentive-Compatible Kidney Exchange in a Slightly Semi-Random Model. EC Avrim Blum, Paul Gölz
2021	J	`jnl`	Incentive-Compatible Kidney Exchange in a Slightly Semi-Random Model. CoRR Avrim Blum, Paul Gölz
2021	A	`conf`	Learning Complexity of Simulated Annealing. AISTATS Avrim Blum, Chen Dan, Saeed Seddighin
2021	A*	`conf`	One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. ICML Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
2021	J	`jnl`	One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. CoRR Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
2021	A*	`conf`	Robust learning under clean-label attack. COLT Avrim Blum, Steve Hanneke, Jian Qian, Han Shao
2021	J	`jnl`	Robust learning under clean-label attack. CoRR Avrim Blum, Steve Hanneke, Jian Qian, Han Shao
2021	J	`jnl`	Stochastic Vertex Cover with Few Queries. CoRR Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan
2021	A*	`conf`	The Strategic Perceptron. EC Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2020	A*	`conf`	Active Local Learning. COLT Arturs Backurs, Avrim Blum, Neha Gupta
2020	J	`jnl`	Active Local Learning. CoRR Arturs Backurs, Avrim Blum, Neha Gupta
2020	A	`conf`	Advancing Subgroup Fairness via Sleeping Experts. ITCS Avrim Blum, Thodoris Lykouris
2020	—	`ch.`	Approximation Stability and Proxy Objectives. Beyond the Worst-Case Analysis of Algorithms Avrim Blum
2020	J	`jnl`	Communication-Aware Collaborative Learning. CoRR Avrim Blum, Shelby Heinecke, Lev Reyzin
2020	J	`jnl`	Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries. Oper. Res. Avrim Blum, John P. Dickerson, Nika Haghtalab, Ariel D. Procaccia, Tuomas Sandholm, Ankit Sharma
2020	J	`jnl`	Kidney exchange and endless paths: On the optimal use of an altruistic donor. CoRR Avrim Blum, Yishay Mansour
2020	J	`jnl`	Learning Complexity of Simulated Annealing. CoRR Avrim Blum, Chen Dan, Saeed Seddighin
2020	J	`jnl`	Lifelong learning in costly feature spaces. Theor. Comput. Sci. Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
2020	J	`jnl`	On the Power of Abstention and Data-Driven Decision Making for Adversarial Robustness. CoRR Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
2020	A*	`conf`	Online Learning with Primary and Secondary Losses. NeurIPS Avrim Blum, Han Shao
2020	J	`jnl`	Online Learning with Primary and Secondary Losses. CoRR Avrim Blum, Han Shao
2020	J	`jnl`	Random Smoothing Might be Unable to Certify L∞ Robustness for High-Dimensional Images. J. Mach. Learn. Res. Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang
2020	J	`jnl`	Random Smoothing Might be Unable to Certify 𝓁 CoRR Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang
2020	—	`conf`	Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? FORC Avrim Blum, Kevin Stangl
2020	J	`jnl`	Technical perspective: Algorithm selection as a learning problem. Commun. ACM Avrim Blum
2020	J	`jnl`	The Strategic Perceptron. CoRR Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
2019	J	`jnl`	Advancing subgroup fairness via sleeping experts. CoRR Avrim Blum, Thodoris Lykouris
2019	A	`conf`	Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem. ESA Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
2019	B	`conf`	Computing Stackelberg Equilibria of Large General-Sum Games. SAGT Avrim Blum, Nika Haghtalab, MohammadTaghi Hajiaghayi, Saeed Seddighin
2019	J	`jnl`	Computing Stackelberg Equilibria of Large General-Sum Games. CoRR Avrim Blum, Nika Haghtalab, MohammadTaghi Hajiaghayi, Saeed Seddighin
2019	A*	`conf`	Optimal Strategies of Blotto Games: Beyond Convexity. EC Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, Mohammad Taghi Hajiaghayi, Christos H. Papadimitriou, Saeed Seddighin
2019	J	`jnl`	Optimal Strategies of Blotto Games: Beyond Convexity. CoRR Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, MohammadTaghi Hajiaghayi, Christos H. Papadimitriou, Saeed Seddighin
2019	J	`jnl`	Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? CoRR Avrim Blum, Kevin Stangl
2019	J	`jnl`	Sparse Approximation via Generating Point Sets. ACM Trans. Algorithms Avrim Blum, Sariel Har-Peled, Benjamin Raichel
2018	A	`ed.`	10th Innovations in Theoretical Computer Science Conference, ITCS 2019, San Diego, California, USA, January 10-12, 2019 ITCS Avrim Blum
2018	A*	`conf`	Active Tolerant Testing. COLT Avrim Blum, Lunjia Hu
2018	A*	`conf`	Algorithms for Generalized Topic Modeling. AAAI Avrim Blum, Nika Haghtalab
2018	A*	`conf`	Approximate Convex Hull of Data Streams. ICALP Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang
2018	J	`jnl`	Bilu-Linial stability, certified algorithms and the Independent Set problem. CoRR Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
2018	A	`conf`	Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems. AAMAS Maria-Florina Balcan, Avrim Blum, Shang-Tse Chen
2018	A*	`conf`	From Battlefields to Elections: Winning Strategies of Blotto and Auditing Games. SODA Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, Mohammad Taghi Hajiaghayi, Mohammad Mahdian, Christos H. Papadimitriou, Ronald L. Rivest, Saeed Seddighin, Philip B. Stark
2018	J	`jnl`	Learning What's Going on: Reconstructing Preferences and Priorities from Opaque Transactions. ACM Trans. Economics and Comput. Avrim Blum, Yishay Mansour, Jamie Morgenstern
2018	A	`conf`	On Price versus Quality. ITCS Avrim Blum, Yishay Mansour
2018	A*	`conf`	On preserving non-discrimination when combining expert advice. NeurIPS Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nati Srebro
2018	J	`jnl`	On preserving non-discrimination when combining expert advice. CoRR Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nathan Srebro
2017	J	`jnl`	Active Tolerant Testing. CoRR Avrim Blum, Lunjia Hu
2017	J	`jnl`	Approximate Convex Hull of Data Streams. CoRR Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang
2017	—	`conf`	Collaborative PAC Learning. NIPS Avrim Blum, Nika Haghtalab, Ariel D. Procaccia, Mingda Qiao
2017	A*	`conf`	Efficient Co-Training of Linear Separators under Weak Dependence. COLT Avrim Blum, Yishay Mansour
2017	A*	`conf`	Efficient PAC Learning from the Crowd. COLT Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
2017	J	`jnl`	Efficient PAC Learning from the Crowd. CoRR Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
2017	B	`conf`	Lifelong Learning in Costly Feature Spaces. ALT Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
2017	J	`jnl`	Lifelong Learning in Costly Feature Spaces. CoRR Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
2017	A*	`conf`	Opting Into Optimal Matchings. SODA Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel D. Procaccia, Eviatar B. Procaccia, Rohit Vaish
2016	J	`jnl`	Generalized Topic Modeling. CoRR Avrim Blum, Nika Haghtalab
2016	A	`conf`	On the Computational Hardness of Manipulating Pairwise Voting Rules. AAMAS Rohit Vaish, Neeldhara Misra, Shivani Agarwal, Avrim Blum
2016	J	`jnl`	Opting Into Optimal Matchings. CoRR Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel D. Procaccia, Eviatar B. Procaccia, Rohit Vaish
2016	—	`ch.`	Semi-supervised Learning. Encyclopedia of Algorithms Avrim Blum
2016	A*	`conf`	Sparse Approximation via Generating Point Sets. SODA Avrim Blum, Sariel Har-Peled, Benjamin Raichel
2015	A*	`conf`	Commitment Without Regrets: Online Learning in Stackelberg Security Games. EC Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
2015	A*	`conf`	Efficient Representations for Lifelong Learning and Autoencoding. COLT Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2015	A*	`conf`	Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries. EC Avrim Blum, John P. Dickerson, Nika Haghtalab, Ariel D. Procaccia, Tuomas Sandholm, Ankit Sharma
2015	A*	`conf`	Learning Valuation Distributions from Partial Observation. AAAI Avrim Blum, Yishay Mansour, Jamie Morgenstern
2015	A*	`conf`	Learning What's Going on: Reconstructing Preferences and Priorities from Opaque Transactions. EC Avrim Blum, Yishay Mansour, Jamie Morgenstern
2015	—	`conf`	Online Allocation and Pricing with Economies of Scale. WINE Avrim Blum, Yishay Mansour, Liu Yang
2015	A	`conf`	Privacy-Preserving Public Information for Sequential Games. ITCS Avrim Blum, Jamie Morgenstern, Ankit Sharma, Adam D. Smith
2015	J	`jnl`	Sparse Approximation via Generating Point Sets. CoRR Avrim Blum, Sariel Har-Peled, Benjamin Raichel
2015	J	`jnl`	Special Issue on New Theoretical Challenges in Machine Learning. Algorithmica Avrim Blum, Philip M. Long
2015	A*	`conf`	The Ladder: A Reliable Leaderboard for Machine Learning Competitions. ICML Avrim Blum, Moritz Hardt
2015	J	`jnl`	The Ladder: A Reliable Leaderboard for Machine Learning Competitions. CoRR Avrim Blum, Moritz Hardt
2014	—	`conf`	Active Learning and Best-Response Dynamics. NIPS Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song
2014	J	`jnl`	Active Learning and Best-Response Dynamics. CoRR Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song
2014	J	`jnl`	Efficient Representations for Life-Long Learning and Autoencoding. CoRR Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2014	A	`conf`	Estimating Accuracy from Unlabeled Data. UAI Emmanouil Antonios Platanios, Avrim Blum, Tom M. Mitchell
2014	J	`jnl`	Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries. CoRR Avrim Blum, Nika Haghtalab, Ariel D. Procaccia, Ankit Sharma
2014	A*	`conf`	Lazy Defenders Are Almost Optimal against Diligent Attackers. AAAI Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
2014	—	`conf`	Learning Mixtures of Ranking Models. NIPS Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan
2014	J	`jnl`	Learning Mixtures of Ranking Models. CoRR Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan
2014	—	`conf`	Learning Optimal Commitment to Overcome Insecurity. NIPS Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
2014	J	`jnl`	Learning Valuation Distributions from Partial Observation. CoRR Avrim Blum, Yishay Mansour, Jamie Morgenstern
2014	J	`jnl`	Learning What's going on: reconstructing preferences and priorities from opaque transactions. CoRR Avrim Blum, Yishay Mansour, Jamie Morgenstern
2014	J	`jnl`	Privacy-Preserving Public Information for Sequential Games. CoRR Avrim Blum, Jamie Morgenstern, Ankit Sharma, Adam D. Smith
2013	J	`jnl`	A learning theory approach to noninteractive database privacy. J. ACM Avrim Blum, Katrina Ligett, Aaron Roth
2013	J	`jnl`	Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior. SIAM J. Comput. Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2013	J	`jnl`	Clustering under approximation stability. J. ACM Maria-Florina Balcan, Avrim Blum, Anupam Gupta
2013	A	`conf`	Differentially private data analysis of social networks via restricted sensitivity. ITCS Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet
2013	—	`conf`	Exploiting Ontology Structures and Unlabeled Data for Learning. ICML (3) Nina Balcan, Avrim Blum, Yishay Mansour
2013	—	`conf`	Fast Private Data Release Algorithms for Sparse Queries. APPROX-RANDOM Avrim Blum, Aaron Roth
2013	A*	`conf`	Harnessing the power of two crossmatches. EC Avrim Blum, Anupam Gupta, Ariel D. Procaccia, Ankit Sharma
2013	A	`conf`	Learnability of DNF with representation-specific queries. ITCS Liu Yang, Avrim Blum, Jaime G. Carbonell
2013	J	`jnl`	The Price of Uncertainty. ACM Trans. Economics and Comput. Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2012	A*	`conf`	Active Property Testing. FOCS Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang
2012	J	`jnl`	Additive Approximation for Near-Perfect Phylogeny Construction CoRR Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet
2012	—	`conf`	Additive Approximation for Near-Perfect Phylogeny Construction. APPROX-RANDOM Pranjal Awasthi, Avrim Blum, Jamie Morgenstern, Or Sheffet
2012	J	`jnl`	Center-based clustering under perturbation stability. Inf. Process. Lett. Pranjal Awasthi, Avrim Blum, Or Sheffet
2012	J	`jnl`	Differentially Private Data Analysis of Social Networks via Restricted Sensitivity CoRR Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet
2012	J	`jnl`	Distributed Learning, Communication Complexity and Privacy CoRR Maria-Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour
2012	A*	`conf`	Distributed Learning, Communication Complexity and Privacy. COLT Maria-Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour
2012	J	`jnl`	The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy CoRR Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet
2012	A*	`conf`	The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy. FOCS Jeremiah Blocki, Avrim Blum, Anupam Datta, Or Sheffet
2011	J	`jnl`	A Learning Theory Approach to Non-Interactive Database Privacy CoRR Avrim Blum, Katrina Ligett, Aaron Roth
2011	J	`jnl`	Active Testing CoRR Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang
2011	J	`jnl`	Fast Private Data Release Algorithms for Sparse Queries CoRR Avrim Blum, Aaron Roth
2011	J	`jnl`	Welfare and Profit Maximization with Production Costs CoRR Avrim Blum, Anupam Gupta, Yishay Mansour, Ankit Sharma
2011	A*	`conf`	Welfare and Profit Maximization with Production Costs. FOCS Avrim Blum, Anupam Gupta, Yishay Mansour, Ankit Sharma
2010	J	`jnl`	A discriminative model for semi-supervised learning. J. ACM Maria-Florina Balcan, Avrim Blum
2010	J	`jnl`	Center-based Clustering under Perturbation Stability CoRR Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	A	`conf`	Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior. ICS Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2010	A*	`conf`	Improved Guarantees for Agnostic Learning of Disjunctions. COLT Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	B	`conf`	On Nash-Equilibria of Approximation-Stable Games. SAGT Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala
2010	J	`jnl`	Routing Without Regret: On Convergence to Nash Equilibria of Regret-Minimizing Algorithms in Routing Games. Theory Comput. Avrim Blum, Eyal Even-Dar, Katrina Ligett
2010	A*	`conf`	Stability Yields a PTAS for k-Median and k-Means Clustering. FOCS Pranjal Awasthi, Avrim Blum, Or Sheffet
2010	—	`conf`	Trading off Mistakes and Don't-Know Predictions. NIPS Amin Sayedi, Morteza Zadimoghaddam, Avrim Blum
2009	A*	`conf`	Approximate clustering without the approximation. SODA Maria-Florina Balcan, Avrim Blum, Anupam Gupta
2009	A*	`conf`	Improved equilibria via public service advertising. SODA Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2009	A*	`conf`	The price of uncertainty. EC Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2009	—	`conf`	Tracking Dynamic Sources of Malicious Activity at Internet Scale. NIPS Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck
2009	J	`jnl`	Veritas: Combining Expert Opinions without Labeled Data. Int. J. Artif. Intell. Tools Sharath R. Cholleti, Sally A. Goldman, Avrim Blum, David G. Politte, Steven Don, Kirk E. Smith, Fred W. Prior
2008	A*	`conf`	A discriminative framework for clustering via similarity functions. STOC Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2008	A*	`conf`	A learning theory approach to non-interactive database privacy. STOC Avrim Blum, Katrina Ligett, Aaron Roth
2008	J	`jnl`	A theory of learning with similarity functions. Mach. Learn. Maria-Florina Balcan, Avrim Blum, Nathan Srebro
2008	B	`conf`	Clustering with Interactive Feedback. ALT Maria-Florina Balcan, Avrim Blum
2008	A*	`conf`	Improved Guarantees for Learning via Similarity Functions. COLT Maria-Florina Balcan, Avrim Blum, Nathan Srebro
2008	A*	`conf`	Item pricing for revenue maximization. EC Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2008	J	`jnl`	Item pricing for revenue maximization. SIGecom Exch. Maria-Florina Balcan, Avrim Blum, Yishay Mansour
2008	A*	`conf`	Limits of Learning-based Signature Generation with Adversaries. NDSS Shobha Venkataraman, Avrim Blum, Dawn Song
2008	J	`jnl`	Reducing mechanism design to algorithm design via machine learning. J. Comput. Syst. Sci. Maria-Florina Balcan, Avrim Blum, Jason D. Hartline, Yishay Mansour
2008	A*	`conf`	Regret minimization and the price of total anarchy. STOC Avrim Blum, MohammadTaghi Hajiaghayi, Katrina Ligett, Aaron Roth
2008	—	`conf`	Veritas: Combining Expert Opinions without Labeled Data. ICTAI (1) Sharath R. Cholleti, Sally A. Goldman, Avrim Blum, David G. Politte, Steven Don
2007	—	`conf`	A Theory of Loss-Leaders: Making Money by Pricing Below Cost. WINE Maria-Florina Balcan, Avrim Blum, T.-H. Hubert Chan, MohammadTaghi Hajiaghayi
2007	B	`conf`	A Theory of Similarity Functions for Learning and Clustering. ALT Avrim Blum
2007	B	`conf`	A Theory of Similarity Functions for Learning and Clustering. Discovery Science Avrim Blum
2007	J	`jnl`	Approximation Algorithms and Online Mechanisms for Item Pricing. Theory Comput. Maria-Florina Balcan, Avrim Blum
2007	J	`jnl`	Approximation Algorithms for Orienteering and Discounted-Reward TSP. SIAM J. Comput. Avrim Blum, Shuchi Chawla, David R. Karger, Terran Lane, Adam Meyerson, Maria Minkoff
2007	A*	`conf`	Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges. EC David J. Abraham, Avrim Blum, Tuomas Sandholm
2007	J	`jnl`	From External to Internal Regret. J. Mach. Learn. Res. Avrim Blum, Yishay Mansour
2007	J	`jnl`	Introduction to the special issue on COLT 2006. Mach. Learn. Avrim Blum, Gábor Lugosi, Hans Ulrich Simon
2007	J	`jnl`	Mechanism design, machine learning, and pricing problems. SIGecom Exch. Maria-Florina Balcan, Avrim Blum
2007	A*	`conf`	Open Problems in Efficient Semi-supervised PAC Learning. COLT Avrim Blum, Maria-Florina Balcan
2007	B	`conf`	Separating Populations with Wide Data: A Spectral Analysis. ISAAC Avrim Blum, Amin Coja-Oghlan, Alan M. Frieze, Shuheng Zhou
2006	—	`conf`	A Random-Surfer Web-Graph Model. ANALCO Avrim Blum, T.-H. Hubert Chan, Mugizi Robert Rwebangira
2006	—	`ch.`	An Augmented PAC Model for Semi-Supervised Learning. Semi-Supervised Learning Maria-Florina Balcan, Avrim Blum
2006	A*	`conf`	Approximation algorithms and online mechanisms for item pricing. EC Maria-Florina Balcan, Avrim Blum
2006	Misc	`conf`	Black Box Anomaly Detection: Is It Utopian?. HotNets Shobha Venkataraman, Juan Caballero, Dawn Song, Avrim Blum, Jennifer Yates
2006	J	`jnl`	Kernels as features: On kernels, margins, and low-dimensional mappings. Mach. Learn. Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2006	A*	`conf`	On a theory of learning with similarity functions. ICML Maria-Florina Balcan, Avrim Blum
2006	J	`jnl`	Online algorithms for market clearing. J. ACM Avrim Blum, Tuomas Sandholm, Martin Zinkevich
2006	A*	`conf`	Routing without regret: on convergence to nash equilibria of regret-minimizing algorithms in routing games. PODC Avrim Blum, Eyal Even-Dar, Katrina Ligett
2005	A*	`conf`	A PAC-Style Model for Learning from Labeled and Unlabeled Data. COLT Maria-Florina Balcan, Avrim Blum
2005	J	`jnl`	Combining Online Algorithms for Acceptance and Rejection. Theory Comput. Yossi Azar, Avrim Blum, David P. Bunde, Yishay Mansour
2005	A*	`conf`	From External to Internal Regret. COLT Avrim Blum, Yishay Mansour
2005	A*	`conf`	Mechanism Design via Machine Learning. FOCS Maria-Florina Balcan, Avrim Blum, Jason D. Hartline, Yishay Mansour
2005	A*	`conf`	Near-optimal online auctions. SODA Avrim Blum, Jason D. Hartline
2005	A*	`conf`	New Streaming Algorithms for Fast Detection of Superspreaders. NDSS Shobha Venkataraman, Dawn Xiaodong Song, Phillip B. Gibbons, Avrim Blum
2005	A*	`conf`	Practical privacy: the SuLQ framework. PODS Avrim Blum, Cynthia Dwork, Frank McSherry, Kobbi Nissim
2005	—	`conf`	Random Projection, Margins, Kernels, and Feature-Selection. SLSFS Avrim Blum
2004	A*	`conf`	Approximation algorithms for deadline-TSP and vehicle routing with time-windows. STOC Nikhil Bansal, Avrim Blum, Shuchi Chawla, Adam Meyerson
2004	—	`conf`	Co-Training and Expansion: Towards Bridging Theory and Practice. NIPS Maria-Florina Balcan, Avrim Blum, Ke Yang
2004	J	`jnl`	Correlation Clustering. Mach. Learn. Nikhil Bansal, Avrim Blum, Shuchi Chawla
2004	A	`conf`	Detection of Interactive Stepping Stones: Algorithms and Confidence Bounds. RAID Avrim Blum, Dawn Xiaodong Song, Shobha Venkataraman
2004	B	`conf`	On Kernels, Margins, and Low-Dimensional Mappings. ALT Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2004	A*	`conf`	Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary. COLT H. Brendan McMahan, Avrim Blum
2004	J	`jnl`	Online learning in online auctions. Theor. Comput. Sci. Avrim Blum, Vijay Kumar, Atri Rudra, Felix Wu
2004	J	`jnl`	Preference Elicitation and Query Learning. J. Mach. Learn. Res. Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich
2004	A*	`conf`	Semi-supervised learning using randomized mincuts. ICML Avrim Blum, John D. Lafferty, Mugizi Robert Rwebangira, Rajashekar Reddy
2003	J	`jnl`	Admission Control to Minimize Rejections. Internet Math. Avrim Blum, Adam Tauman Kalai, Jon M. Kleinberg
2003	A*	`conf`	Approximation Algorithms for Orienteering and Discounted-Reward TSP. FOCS Avrim Blum, Shuchi Chawla, David R. Karger, Terran Lane, Adam Meyerson, Maria Minkoff
2003	B	`conf`	Combining online algorithms for rejection and acceptance. SPAA Yossi Azar, Avrim Blum, Yishay Mansour
2003	A*	`conf`	Learning a Function of r Relevant Variables. COLT Avrim Blum
2003	A*	`conf`	Machine Learning: My Favorite Results, Directions, and Open Problems. FOCS Avrim Blum
2003	J	`jnl`	Microchoice Bounds and Self Bounding Learning Algorithms. Mach. Learn. John Langford, Avrim Blum
2003	J	`jnl`	Noise-tolerant learning, the parity problem, and the statistical query model. J. ACM Avrim Blum, Adam Kalai, Hal Wasserman
2003	J	`jnl`	On Statistical Query Sampling and NMR Quantum Computing Electron. Colloquium Comput. Complex. Avrim Blum, Ke Yang
2003	A	`conf`	On Statistical Query Sampling and NMR Quantum Computing. CCC Ke Yang, Avrim Blum
2003	A*	`conf`	On polynomial-time preference elicitation with value queries. EC Martin Zinkevich, Avrim Blum, Tuomas Sandholm
2003	A*	`conf`	Online learning in online auctions. SODA Avrim Blum, Vijay Kumar, Atri Rudra, Felix Wu
2003	B	`conf`	Online oblivious routing. SPAA Nikhil Bansal, Avrim Blum, Shuchi Chawla, Adam Meyerson
2003	A*	`conf`	PAC-MDL Bounds. COLT Avrim Blum, John Langford
2003	A*	`conf`	Planning in the Presence of Cost Functions Controlled by an Adversary. ICML H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
2003	A*	`conf`	Preference Elicitation and Query Learning. COLT Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich
2003	A	`conf`	Scheduling for Flow-Time with Admission Control. ESA Nikhil Bansal, Avrim Blum, Shuchi Chawla, Kedar Dhamdhere
2003	J	`jnl`	Static Optimality and Dynamic Search-Optimality in Lists and Trees. Algorithmica Avrim Blum, Shuchi Chawla, Adam Kalai
2002	A*	`conf`	Correlation Clustering. FOCS Nikhil Bansal, Avrim Blum, Shuchi Chawla
2002	A*	`conf`	Online algorithms for market clearing. SODA Avrim Blum, Tuomas Sandholm, Martin Zinkevich
2002	A*	`conf`	Smoothed analysis of the perceptron algorithm for linear programming. SODA Avrim Blum, John Dunagan
2002	A*	`conf`	Static optimality and dynamic search-optimality in lists and trees. SODA Avrim Blum, Shuchi Chawla, Adam Kalai
2001	B	`conf`	Admission Control to Minimize Rejections. WADS Avrim Blum, Adam Kalai, Jon M. Kleinberg
2001	A*	`conf`	Learning from Labeled and Unlabeled Data using Graph Mincuts. ICML Avrim Blum, Shuchi Chawla
2000	J	`jnl`	A Decomposition Theorem for Task Systems and Bounds for Randomized Server Problems. SIAM J. Comput. Avrim Blum, Howard J. Karloff, Yuval Rabani, Michael E. Saks
2000	J	`jnl`	An Online Algorithm for Improving Performance in Navigation. SIAM J. Comput. Avrim Blum, Prasad Chalasani
2000	A*	`conf`	FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness. ICML Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum
2000	J	`jnl`	Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model CoRR Avrim Blum, Adam Kalai, Hal Wasserman
2000	A*	`conf`	Noise-tolerant learning, the parity problem, and the statistical query model. STOC Avrim Blum, Adam Kalai, Hal Wasserman
2000	J	`jnl`	On-line Learning and the Metrical Task System Problem. Mach. Learn. Avrim Blum, Carl Burch
2000	J	`jnl`	Semi-definite relaxations for minimum bandwidth and other vertex-ordering problems. Theor. Comput. Sci. Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala
1999	J	`jnl`	A Constant-Factor Approximation Algorithm for the J. Comput. Syst. Sci. Avrim Blum, R. Ravi, Santosh S. Vempala
1999	A*	`conf`	Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation. COLT Avrim Blum, Adam Kalai, John Langford
1999	A*	`conf`	Finely-Competitive Paging. FOCS Avrim Blum, Carl Burch, Adam Kalai
1999	A*	`conf`	Microchoice Bounds and Self Bounding Learning Algorithms. COLT John Langford, Avrim Blum
1999	Misc	`conf`	On-line algorithms for combining language models. ICASSP Adam Kalai, Stanley F. Chen, Avrim Blum, Ronald Rosenfeld
1999	—	`conf`	Probabilistic Planning in the Graphplan Framework. ECP Avrim Blum, John Langford
1999	J	`jnl`	Universal Portfolios With and Without Transaction Costs. Mach. Learn. Avrim Blum, Adam Kalai
1998	J	`jnl`	A Constant-Factor Approximation Algorithm for the Geometric k-MST Problem in the Plane. SIAM J. Comput. Joseph S. B. Mitchell, Avrim Blum, Prasad Chalasani, Santosh S. Vempala
1998	J	`jnl`	A Note on Learning from Multiple-Instance Examples. Mach. Learn. Avrim Blum, Adam Kalai
1998	J	`jnl`	A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. Algorithmica Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
1998	A*	`conf`	Combining Labeled and Unlabeled Data with Co-Training. COLT Avrim Blum, Tom M. Mitchell
1998	J	`jnl`	Learning with Unreliable Boundary Queries. J. Comput. Syst. Sci. Avrim Blum, Prasad Chalasani, Sally A. Goldman, Donna K. Slonim
1998	J	`jnl`	New Approximation Guarantees for Minimum-Weight k-Trees and Prize-Collecting Salesmen. SIAM J. Comput. Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala
1998	A*	`conf`	On Learning Monotone Boolean Functions. FOCS Avrim Blum, Carl Burch, John Langford
1998	J	`jnl`	On Learning Read-k-Satisfy-j DNF. SIAM J. Comput. Howard Aizenstein, Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth
1998	J	`jnl`	On a theory of computing symposia. SIGACT News Avrim Blum, Prabhakar Raghavan
1998	A*	`conf`	Semi-Definite Relaxations for Minimum Bandwidth and other Vertex-Ordering Problems. STOC Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala
1997	A*	`conf`	A polylog( STOC Yair Bartal, Avrim Blum, Carl Burch, Andrew Tomkins
1997	J	`jnl`	An Õ(n^{3/14})-Coloring Algorithm for 3-Colorable Graphs. Inf. Process. Lett. Avrim Blum, David R. Karger
1997	J	`jnl`	Empirical Support for Winnow and Weighted-Majority Algorithms: Results on a Calendar Scheduling Domain. Mach. Learn. Avrim Blum
1997	J	`jnl`	Fast Planning Through Planning Graph Analysis. Artif. Intell. Avrim Blum, Merrick L. Furst
1997	J	`jnl`	Learning an Intersection of a Constant Number of Halfspaces over a Uniform Distribution. J. Comput. Syst. Sci. Avrim Blum, Ravindran Kannan
1997	J	`jnl`	Navigating in Unfamiliar Geometric Terrain. SIAM J. Comput. Avrim Blum, Prabhakar Raghavan, Baruch Schieber
1997	A*	`conf`	On-line Learning and the Metrical Task System Problem. COLT Avrim Blum, Carl Burch
1997	J	`jnl`	Selection of Relevant Features and Examples in Machine Learning. Artif. Intell. Avrim Blum, Pat Langley
1997	A*	`conf`	Universal Portfolios With and Without Transaction Costs. COLT Avrim Blum, Adam Kalai
1996	A*	`conf`	A Constant-factor Approximation Algorithm for the STOC Avrim Blum, R. Ravi, Santosh S. Vempala
1996	A*	`conf`	A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. FOCS Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
1996	—	`conf`	On-line Algorithms in Machine Learning. Online Algorithms Avrim Blum
1996	A*	`ed.`	Proceedings of the Ninth Annual Conference on Computational Learning Theory, COLT 1996, Desenzano del Garda, Italy, June 28-July 1, 1996. COLT Avrim Blum, Michael J. Kearns
1996	A*	`conf`	Randomized Robot Navigation Algorithms. SODA Piotr Berman, Avrim Blum, Amos Fiat, Howard J. Karloff, Adi Rosén, Michael E. Saks
1995	A*	`conf`	A constant-factor approximation for the STOC Avrim Blum, Prasad Chalasani, Santosh S. Vempala
1995	J	`jnl`	Coloring Random and Semi-Random k-Colorable Graphs. J. Algorithms Avrim Blum, Joel Spencer
1995	A*	`conf`	Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain. ICML Avrim Blum
1995	J	`jnl`	Fast Learning of k-Term DNF Formulas with Queries. J. Comput. Syst. Sci. Avrim Blum, Steven Rudich
1995	A*	`conf`	Fast Planning Through Planning Graph Analysis. IJCAI Avrim Blum, Merrick L. Furst
1995	A*	`conf`	Improved approximation guarantees for minimum-weight STOC Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala
1995	J	`jnl`	Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes. J. Comput. Syst. Sci. Avrim Blum, Lisa Hellerstein, Nick Littlestone
1995	A*	`conf`	Learning with Unreliable Boundary Queries. COLT Avrim Blum, Prasad Chalasani, Sally A. Goldman, Donna K. Slonim
1994	J	`jnl`	An on-line algorithm for improving performance in navigation. CoRR Avrim Blum, Prasad Chalasani
1994	J	`jnl`	Linear Approximation of Shortest Superstrings. J. ACM Avrim Blum, Tao Jiang, Ming Li, John Tromp, Mihalis Yannakakis
1994	J	`jnl`	New Approximation Algorithms for Graph Coloring. J. ACM Avrim Blum
1994	A*	`conf`	On Learning Read- COLT Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth
1994	J	`jnl`	On the minimum latency problem. CoRR Avrim Blum, Prasad Chalasani, Don Coppersmith, William R. Pulleyblank, Prabhakar Raghavan, Madhu Sudan
1994	J	`jnl`	Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain. SIAM J. Comput. Avrim Blum
1994	A*	`conf`	The minimum latency problem. STOC Avrim Blum, Prasad Chalasani, Don Coppersmith, William R. Pulleyblank, Prabhakar Raghavan, Madhu Sudan
1994	A*	`conf`	Weakly learning DNF and characterizing statistical query learning using Fourier analysis. STOC Avrim Blum, Merrick L. Furst, Jeffrey C. Jackson, Michael J. Kearns, Yishay Mansour, Steven Rudich
1993	A*	`conf`	An On-Line Algorithm for Improving Performance in Navigation FOCS Avrim Blum, Prasad Chalasani
1993	A*	`conf`	Cryptographic Primitives Based on Hard Learning Problems. CRYPTO Avrim Blum, Merrick L. Furst, Michael J. Kearns, Richard J. Lipton
1993	A*	`conf`	Learning an Intersection of k Halfspaces over a Uniform Distribution FOCS Avrim Blum, Ravi Kannan
1993	A*	`conf`	On Learning Embedded Symmetric Concepts. COLT Avrim Blum, Prasad Chalasani, Jeffrey C. Jackson
1993	—	`conf`	Training a 3-Node Neural Network is NP-Complete. Machine Learning: From Theory to Applications Avrim Blum, Ronald L. Rivest
1992	A*	`conf`	A Decomposition Theorem and Bounds for Randomized Server Problems FOCS Avrim Blum, Howard J. Karloff, Yuval Rabani, Michael E. Saks
1992	A*	`conf`	Fast Learning of k-Term DNF Formulas with Queries STOC Avrim Blum, Steven Rudich
1992	J	`jnl`	Learning Boolean Functions in an Infinite Attribute Space. Mach. Learn. Avrim Blum
1992	A*	`conf`	Learning Switching Concepts. COLT Avrim Blum, Prasad Chalasani
1992	J	`jnl`	Rank-r Decision Trees are a Subclass of r-Decision Lists. Inf. Process. Lett. Avrim Blum
1992	J	`jnl`	Training a 3-node neural network is NP-complete. Neural Networks Avrim Blum, Ronald L. Rivest
1991	A*	`conf`	Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes. COLT Avrim Blum, Lisa Hellerstein, Nick Littlestone
1991	A*	`conf`	Linear Approximation of Shortest Superstrings STOC Avrim Blum, Tao Jiang, Ming Li, John Tromp, Mihalis Yannakakis
1991	—	`conf`	Navigating in Unfamiliar Geometric Terrain (Extended Summary). On-Line Algorithms Avrim Blum, Prabhakar Raghavan, Baruch Schieber
1991	A*	`conf`	Navigating in Unfamiliar Geometric Terrain (Preliminary Version) STOC Avrim Blum, Prabhakar Raghavan, Baruch Schieber
1990	A*	`conf`	Learning Boolean Functions in an Infinite Atribute Space (Extended Abstract) STOC Avrim Blum
1990	A*	`conf`	Learning Functions of COLT Avrim Blum, Mona Singh
1990	A*	`conf`	Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain FOCS Avrim Blum
1990	A*	`conf`	Separating PAC and Mistake-Bound Learning Models Over the Boolean Domain (Abstract). COLT Avrim Blum
1990	A*	`conf`	Some Tools for Approximate 3-Coloring (Extended Abstract) FOCS Avrim Blum
1989	A*	`conf`	An \tildeO(n^0.4)-Approximation Algorithm for 3-Coloring (and Improved Approximation Algorithm for k-Coloring) STOC Avrim Blum
1988	A*	`conf`	Training a 3-Node Neural Network is NP-Complete. COLT Avrim Blum, Ronald L. Rivest
1988	—	`conf`	Training a 3-Node Neural Network is NP-Complete. NIPS Avrim Blum, Ronald L. Rivest