Avrim Blum

ORCID

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 95

Top Venues

CoRR

NeurIPS

COLT

Publications

Avrim Blum, Melissa Dutz
Winning Without Observing Payoffs: Exploiting Behavioral Biases to Win Nearly Every Round. ITCS (2024)
Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin Stangl
On the Vulnerability of Fairness Constrained Learning to Malicious Noise. CoRR (2023)
Han Shao, Avrim Blum, Omar Montasser
Strategic Classification under Unknown Personalized Manipulation. CoRR (2023)
Saba Ahmadi, Avrim Blum, Kunhe Yang
Fundamental Bounds on Online Strategic Classification. EC (2023)
Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin Stangl
Certifiable (Multi)Robustness Against Patch Attacks Using ERM. CoRR (2023)
Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. CoRR (2023)
Han Shao, Avrim Blum, Omar Montasser
Strategic Classification under Unknown Personalized Manipulation. NeurIPS (2023)
Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang
Dueling Optimization with a Monotone Adversary. CoRR (2023)
Saba Ahmadi, Avrim Blum, Kunhe Yang
Fundamental Bounds on Online Strategic Classification. CoRR (2023)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
Setting Fair Incentives to Maximize Improvement. FORC (2023)
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
An Analysis of Robustness of Non-Lipschitz Networks. J. Mach. Learn. Res. 24 (2023)
Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. NeurIPS (2023)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
On Classification of Strategic Agents Who Can Both Game and Improve. FORC (2022)
Han Shao, Omar Montasser, Avrim Blum
A Theory of PAC Learnability under Transformation Invariances. NeurIPS (2022)
Avrim Blum, Kevin Stangl, Ali Vakilian
Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. FAccT (2022)
Avrim Blum, Kevin Stangl, Ali Vakilian
Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipeline. CoRR (2022)
Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. CoRR (2022)
Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
Robustly-reliable learners under poisoning attacks. CoRR (2022)
Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan
Stochastic Vertex Cover with Few Queries. SODA (2022)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
On classification of strategic agents who can both game and improve. CoRR (2022)
Maria-Florina Balcan, Avrim Blum, Steve Hanneke, Dravyansh Sharma
Robustly-reliable learners under poisoning attacks. COLT (2022)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
Setting Fair Incentives to Maximize Improvement. CoRR (2022)
Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. NeurIPS (2022)
Han Shao, Omar Montasser, Avrim Blum
A Theory of PAC Learnability under Transformation Invariances. CoRR (2022)
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. CoRR (2021)
Avrim Blum, Paul Gölz
Incentive-Compatible Kidney Exchange in a Slightly Semi-Random Model. EC (2021)
Avrim Blum, Chen Dan, Saeed Seddighin
Learning Complexity of Simulated Annealing. AISTATS (2021)
Avrim Blum, Paul Gölz
Incentive-Compatible Kidney Exchange in a Slightly Semi-Random Model. CoRR (2021)
Naren Manoj, Avrim Blum
Excess Capacity and Backdoor Poisoning. NeurIPS (2021)
Avrim Blum, Shelby Heinecke, Lev Reyzin
Communication-Aware Collaborative Learning. AAAI (2021)
Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan
Stochastic Vertex Cover with Few Queries. CoRR (2021)
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. ICML (2021)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
The Strategic Perceptron. EC (2021)
Naren Sarayu Manoj, Avrim Blum
Excess Capacity and Backdoor Poisoning. CoRR (2021)
Avrim Blum, Steve Hanneke, Jian Qian, Han Shao
Robust learning under clean-label attack. COLT (2021)
Avrim Blum, Steve Hanneke, Jian Qian, Han Shao
Robust learning under clean-label attack. CoRR (2021)
Avrim Blum, Han Shao
Online Learning with Primary and Secondary Losses. NeurIPS (2020)
Avrim Blum, Han Shao
Online Learning with Primary and Secondary Losses. CoRR (2020)
Avrim Blum, Yishay Mansour
Kidney exchange and endless paths: On the optimal use of an altruistic donor. CoRR (2020)
Avrim Blum, John P. Dickerson, Nika Haghtalab, Ariel D. Procaccia, Tuomas Sandholm, Ankit Sharma
Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries. Oper. Res. 68 (1) (2020)
Arturs Backurs, Avrim Blum, Neha Gupta
Active Local Learning. CoRR (2020)
Arturs Backurs, Avrim Blum, Neha Gupta
Active Local Learning. COLT (2020)
Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang
Robustness for High-Dimensional Images. CoRR (2020)
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
The Strategic Perceptron. CoRR (2020)
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang
On the Power of Abstention and Data-Driven Decision Making for Adversarial Robustness. CoRR (2020)
Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang
Random Smoothing Might be Unable to Certify L∞ Robustness for High-Dimensional Images. J. Mach. Learn. Res. 21 (2020)
Avrim Blum, Shelby Heinecke, Lev Reyzin
Communication-Aware Collaborative Learning. CoRR (2020)
Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
Lifelong learning in costly feature spaces. Theor. Comput. Sci. 808 (2020)
Avrim Blum
Technical perspective: Algorithm selection as a learning problem. Commun. ACM 63 (6) (2020)
Avrim Blum, Chen Dan, Saeed Seddighin
Learning Complexity of Simulated Annealing. CoRR (2020)
Avrim Blum, Thodoris Lykouris
Advancing Subgroup Fairness via Sleeping Experts. ITCS (2020)
Avrim Blum, Kevin Stangl
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? FORC (2020)
Avrim Blum, Nika Haghtalab, MohammadTaghi Hajiaghayi, Saeed Seddighin
Computing Stackelberg Equilibria of Large General-Sum Games. SAGT (2019)
Avrim Blum, Thodoris Lykouris
Advancing subgroup fairness via sleeping experts. CoRR (2019)
Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem. ESA (2019)
Avrim Blum, Nika Haghtalab, MohammadTaghi Hajiaghayi, Saeed Seddighin
Computing Stackelberg Equilibria of Large General-Sum Games. CoRR (2019)
Avrim Blum, Sariel Har-Peled, Benjamin Raichel
Sparse Approximation via Generating Point Sets. ACM Trans. Algorithms 15 (3) (2019)
Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, MohammadTaghi Hajiaghayi, Christos H. Papadimitriou, Saeed Seddighin
Optimal Strategies of Blotto Games: Beyond Convexity. CoRR (2019)
Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, Mohammad Taghi Hajiaghayi, Christos H. Papadimitriou, Saeed Seddighin
Optimal Strategies of Blotto Games: Beyond Convexity. EC (2019)
Avrim Blum, Kevin Stangl
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? CoRR (2019)
Soheil Behnezhad, Avrim Blum, Mahsa Derakhshan, Mohammad Taghi Hajiaghayi, Mohammad Mahdian, Christos H. Papadimitriou, Ronald L. Rivest, Saeed Seddighin, Philip B. Stark
From Battlefields to Elections: Winning Strategies of Blotto and Auditing Games. SODA (2018)
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nati Srebro
On preserving non-discrimination when combining expert advice. NeurIPS (2018)
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nathan Srebro
On preserving non-discrimination when combining expert advice. CoRR (2018)
Avrim Blum, Lunjia Hu
Active Tolerant Testing. COLT (2018)
Avrim Blum, Nika Haghtalab
Algorithms for Generalized Topic Modeling. AAAI (2018)
Avrim Blum, Yishay Mansour, Jamie Morgenstern
Learning What's Going on: Reconstructing Preferences and Priorities from Opaque Transactions. ACM Trans. Economics and Comput. 6 (3-4) (2018)
Avrim Blum, Yishay Mansour
On Price versus Quality. ITCS (2018)
Maria-Florina Balcan, Avrim Blum, Shang-Tse Chen
Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems. AAMAS (2018)
Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan
Bilu-Linial stability, certified algorithms and the Independent Set problem. CoRR (2018)
Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang
Approximate Convex Hull of Data Streams. ICALP (2018)
Avrim Blum, Nika Haghtalab, Ariel D. Procaccia, Mingda Qiao
Collaborative PAC Learning. NIPS (2017)
Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
Efficient PAC Learning from the Crowd. COLT (2017)
Avrim Blum, Lunjia Hu
Active Tolerant Testing. CoRR (2017)
Avrim Blum, Yishay Mansour
Efficient Co-Training of Linear Separators under Weak Dependence. COLT (2017)
Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
Lifelong Learning in Costly Feature Spaces. CoRR (2017)
Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan
Lifelong Learning in Costly Feature Spaces. ALT (2017)
Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel D. Procaccia, Eviatar B. Procaccia, Rohit Vaish
Opting Into Optimal Matchings. SODA (2017)
Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour
Efficient PAC Learning from the Crowd. CoRR (2017)
Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang
Approximate Convex Hull of Data Streams. CoRR (2017)
Avrim Blum, Sariel Har-Peled, Benjamin Raichel
Sparse Approximation via Generating Point Sets. SODA (2016)
Avrim Blum, Nika Haghtalab
Generalized Topic Modeling. CoRR (2016)
Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel D. Procaccia, Eviatar B. Procaccia, Rohit Vaish
Opting Into Optimal Matchings. CoRR (2016)
Rohit Vaish, Neeldhara Misra, Shivani Agarwal, Avrim Blum
On the Computational Hardness of Manipulating Pairwise Voting Rules. AAMAS (2016)
Avrim Blum, Jamie Morgenstern, Ankit Sharma, Adam D. Smith
Privacy-Preserving Public Information for Sequential Games. ITCS (2015)
Avrim Blum, Yishay Mansour, Liu Yang
Online Allocation and Pricing with Economies of Scale. WINE (2015)
Avrim Blum, Philip M. Long
Special Issue on New Theoretical Challenges in Machine Learning. Algorithmica 72 (1) (2015)
Avrim Blum, Yishay Mansour, Jamie Morgenstern
Learning What's Going on: Reconstructing Preferences and Priorities from Opaque Transactions. EC (2015)
Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
Commitment Without Regrets: Online Learning in Stackelberg Security Games. EC (2015)
Avrim Blum, Yishay Mansour, Jamie Morgenstern
Learning Valuation Distributions from Partial Observation. AAAI (2015)
Avrim Blum, Sariel Har-Peled, Benjamin Raichel
Sparse Approximation via Generating Point Sets. CoRR (2015)
Avrim Blum, Moritz Hardt
The Ladder: A Reliable Leaderboard for Machine Learning Competitions. ICML (2015)
Avrim Blum, John P. Dickerson, Nika Haghtalab, Ariel D. Procaccia, Tuomas Sandholm, Ankit Sharma
Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries. EC (2015)
Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
Variational Dropout and the Local Reparameterization Trick. NIPS (2015)
Avrim Blum, Moritz Hardt
The Ladder: A Reliable Leaderboard for Machine Learning Competitions. CoRR (2015)
Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
Efficient Representations for Lifelong Learning and Autoencoding. COLT (2015)
Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
Efficient Representations for Life-Long Learning and Autoencoding. CoRR (2014)
Emmanouil Antonios Platanios, Avrim Blum, Tom M. Mitchell
Estimating Accuracy from Unlabeled Data. UAI (2014)
Avrim Blum, Nika Haghtalab, Ariel D. Procaccia
Lazy Defenders Are Almost Optimal against Diligent Attackers. AAAI (2014)
Avrim Blum, Yishay Mansour, Jamie Morgenstern
Learning What's going on: reconstructing preferences and priorities from opaque transactions. CoRR (2014)
Maria-Florina Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song
Active Learning and Best-Response Dynamics. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Avrim Blum