Miroslav Dudík

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 55

Top Topics

Budget Constraints

Policy Evaluation

Integer Programming

Prediction Markets

Top Venues

Publications

Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík
A structured regression approach for evaluating model performance across intersectional subgroups. CoRR (2024)
Nataly Brukhim, Miroslav Dudík, Aldo Pacchiano, Robert E. Schapire
A Unified Model and Dimension for Interactive Estimation. CoRR (2023)
Hilde J. P. Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio
Fairlearn: Assessing and Improving Fairness of AI Systems. CoRR (2023)
Hilde J. P. Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio
Fairlearn: Assessing and Improving Fairness of AI Systems. J. Mach. Learn. Res. 24 (2023)
Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning. ICML (2022)
Miroslav Dudík, Ziwei Ji, Robert E. Schapire, Matus Telgarsky
Convex Analysis at Infinity: An Introduction to Astral Space. CoRR (2022)
Madalina Vlasceanu, Miroslav Dudík, Ida Momennejad
Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations. FAccT (2022)
Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization. CoRR (2022)
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS (2021)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. ICML (2021)
Miroslav Dudík, Xintong Wang, David M. Pennock, David M. Rothschild
Log-time Prediction Markets for Interval Securities. CoRR (2021)
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR (2021)
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf
Responsible computing during COVID-19 and beyond. Commun. ACM 64 (7) (2021)
Miroslav Dudík, Xintong Wang, David M. Pennock, David M. Rothschild
Log-time Prediction Markets for Interval Securities. AAMAS (2021)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. CoRR (2021)
Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
Gradient descent follows the regularization path for general losses. COLT (2020)
Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
Constrained episodic reinforcement learning in concave-convex and knapsack settings. CoRR (2020)
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík
Doubly robust off-policy evaluation with shrinkage. ICML (2020)
Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
Gradient descent follows the regularization path for general losses. CoRR (2020)
Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
Constrained episodic reinforcement learning in concave-convex and knapsack settings. NeurIPS (2020)
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík
Doubly robust off-policy evaluation with shrinkage. CoRR (2019)
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
Reinforcement Learning with Convex Constraints. NeurIPS (2019)
Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms. ICML (2019)
Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford
Provably efficient RL with Rich Observations via Latent State Decoding. ICML (2019)
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
Reinforcement Learning with Convex Constraints. CoRR (2019)
Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu
Fair Regression: Quantitative Definitions and Reduction-based Algorithms. CoRR (2019)
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI (2019)
Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford
Provably efficient RL with Rich Observations via Latent State Decoding. CoRR (2019)
Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III
Hierarchical Imitation and Reinforcement Learning. ICML (2018)
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
Practical Contextual Bandits with Regression Oracles. ICML (2018)
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
Improving fairness in machine learning systems: What do industry practitioners need? CoRR (2018)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. ICML (2018)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. CoRR (2018)
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
Practical Contextual Bandits with Regression Oracles. CoRR (2018)
Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III
Hierarchical Imitation and Reinforcement Learning. CoRR (2018)
Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
A Decomposition of Forecast Error in Prediction Markets. CoRR (2017)
Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui
The group k-support norm for learning with structured sparsity. ICASSP (2017)
Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
A Decomposition of Forecast Error in Prediction Markets. NIPS (2017)
Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudík
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits. ICML (2017)
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-Efficient Online Learning and Auction Design. FOCS (2017)
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
Off-policy evaluation for slate recommendation. NIPS (2017)
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-Efficient Learning and Auction Design. CoRR (2016)
Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan
Arbitrage-Free Combinatorial Market Making via Integer Programming. EC (2016)
Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík
Contextual semibandits via supervised learning oracles. NIPS (2016)
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
Off-policy evaluation for slate recommendation. CoRR (2016)
Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudík
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits. CoRR (2016)
Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan
Arbitrage-Free Combinatorial Market Making via Integer Programming. CoRR (2016)
Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík
Efficient Contextual Semi-Bandit Learning. CoRR (2015)
Matus Telgarsky, Miroslav Dudík, Robert E. Schapire
Convex Risk Minimization and Conditional Probability Estimation. CoRR (2015)
Nikhil R. Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock
Budget Constraints in Prediction Markets. UAI (2015)
Nikhil R. Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock
Budget Constraints in Prediction Markets. CoRR (2015)
Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Contextual Dueling Bandits. CoRR (2015)
Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Contextual Dueling Bandits. COLT (2015)
Matus Telgarsky, Miroslav Dudík
Convex Risk Minimization and Conditional Probability Estimation. COLT (2015)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Doubly Robust Policy Evaluation and Optimization. CoRR (2015)
Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford
A reliable effective terascale linear learning system. J. Mach. Learn. Res. 15 (1) (2014)
Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
Market Making with Decreasing Utility for Information. UAI (2014)
Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins
Robust Multi-objective Learning with Mentor Feedback. COLT (2014)
Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
Market Making with Decreasing Utility for Information. CoRR (2014)
Miroslav Dudík, Sébastien Lahaie, David M. Pennock, David M. Rothschild
A combinatorial prediction market for the U.S. elections. EC (2013)
Alekh Agarwal, Léon Bottou, Miroslav Dudík, John Langford
Para-active learning. CoRR (2013)
Brian D. Ziebart, Miroslav Dudík, Geoffrey J. Gordon, Katia P. Sycara, Wendi L. Adair, Jeanne M. Brett
Identifying Culture and Leveraging Cultural Differences for Negotiation Agents. HICSS (2012)
Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick
Lifted coordinate descent for learning with trace-norm regularization. AISTATS (2012)
Miroslav Dudík, Geoffrey J. Gordon
A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games CoRR (2012)
Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick
Large-scale image classification with trace-norm regularization. CVPR (2012)
Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík
First-Order Mixed Integer Linear Programming CoRR (2012)
Miroslav Dudík, Sébastien Lahaie, David M. Pennock
A tractable combinatorial market maker using constraint generation. EC (2012)
Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
Contextual Bandit Learning with Predictable Rewards. AISTATS (2012)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. UAI (2012)
Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits CoRR (2012)
Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
Contextual Bandit Learning with Predictable Rewards CoRR (2012)
Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
Efficient Optimal Learning for Contextual Bandits. UAI (2011)
Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford
A Reliable Effective Terascale Linear Learning System CoRR (2011)
Miroslav Dudík, John Langford, Lihong Li
Doubly Robust Policy Evaluation and Learning CoRR (2011)
Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
Efficient Optimal Learning for Contextual Bandits CoRR (2011)
Roie Zivan, Miroslav Dudík, Praveen Paruchuri, Katia P. Sycara
Maximizing revenue in symmetric resource allocation systems when user utilities exhibit diminishing returns. AAMAS (2011)
Miroslav Dudík, John Langford, Lihong Li
Doubly Robust Policy Evaluation and Learning. ICML (2011)
Roie Zivan, Miroslav Dudík, Steven Okamoto, Katia P. Sycara
Reducing Untruthful Manipulation in Envy-Free Pareto Optimal Resource Allocation. IAT (2010)
Miroslav Dudík, Geoffrey J. Gordon
A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games. UAI (2009)
Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík
First-Order Mixed Integer Linear Programming. UAI (2009)
Miroslav Dudík, Steven J. Phillips
Generative and Discriminative Learning with Unknown Labeling Bias. NIPS (2008)
Miroslav Dudík, David M. Blei, Robert E. Schapire
Hierarchical maximum entropy density estimation. ICML (2007)
Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling. J. Mach. Learn. Res. 8 (2007)
Jonathan D. Chang, Miroslav Dudík, David M. Blei
PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks. SemEval@ACL (2007)
Miroslav Dudík, Robert E. Schapire
Maximum Entropy Distribution Estimation with Generalized Regularization. COLT (2006)
Miroslav Dudík, Robert E. Schapire, Steven J. Phillips
Correcting sample selection bias in maximum entropy density estimation. NIPS (2005)
Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
Performance Guarantees for Regularized Maximum Entropy Density Estimation. COLT (2004)
Steven J. Phillips, Miroslav Dudík, Robert E. Schapire
A maximum entropy approach to species distribution modeling. ICML (2004)
Miroslav Dudík, Leonard J. Schulman
Reconstruction from subsequences. J. Comb. Theory, Ser. A 103 (2) (2003)