Miroslav Dudík

98 papers A* 29A 11B 1Misc 1Journal 46Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum. CoRR Nived Rajaraman, Audrey Huang, Miroslav Dudík, Robert E. Schapire, Dylan J. Foster, Akshay Krishnamurthy
2025	B	`conf`	FairnessEval: a Framework for Evaluating Fairness of Machine Learning Models. EDBT Andrea Baraldi, Matteo Brucato, Miroslav Dudík, Francesco Guerra, Matteo Interlandi
2025	A*	`conf`	On the Hardness of Bandit Learning. COLT Nataly Brukhim, Aldo Pacchiano, Miroslav Dudík, Robert E. Schapire
2025	J	`jnl`	On the Hardness of Bandit Learning. CoRR Nataly Brukhim, Aldo Pacchiano, Miroslav Dudík, Robert E. Schapire
2024	—	`conf`	A structured regression approach for evaluating model performance across intersectional subgroups. FAccT Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík
2024	J	`jnl`	A structured regression approach for evaluating model performance across intersectional subgroups. CoRR Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík
2024	A*	`conf`	PcLast: Discovering Plannable Continuous Latent States. ICML Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miroslav Dudík, John Langford, Alex Lamb
2024	J	`jnl`	SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation. CoRR Mikhail Khodak, Lester Mackey, Alexandra Chouldechova, Miroslav Dudík
2023	J	`jnl`	A Unified Model and Dimension for Interactive Estimation. CoRR Nataly Brukhim, Miroslav Dudík, Aldo Pacchiano, Robert E. Schapire
2023	J	`jnl`	Fairlearn: Assessing and Improving Fairness of AI Systems. CoRR Hilde J. P. Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio
2023	J	`jnl`	Fairlearn: Assessing and Improving Fairness of AI Systems. J. Mach. Learn. Res. Hilde J. P. Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio
2022	J	`jnl`	Convex Analysis at Infinity: An Introduction to Astral Space. CoRR Miroslav Dudík, Ziwei Ji, Robert E. Schapire, Matus Telgarsky
2022	—	`conf`	Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations. FAccT Madalina Vlasceanu, Miroslav Dudík, Ida Momennejad
2022	A*	`conf`	Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning. ICML Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
2022	J	`jnl`	Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization. CoRR Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu
2021	A*	`conf`	Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	J	`jnl`	Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	A*	`conf`	Interactive Learning from Activity Description. ICML Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
2021	J	`jnl`	Interactive Learning from Activity Description. CoRR Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
2021	A	`conf`	Log-time Prediction Markets for Interval Securities. AAMAS Miroslav Dudík, Xintong Wang, David M. Pennock, David M. Rothschild
2021	J	`jnl`	Log-time Prediction Markets for Interval Securities. CoRR Miroslav Dudík, Xintong Wang, David M. Pennock, David M. Rothschild
2021	J	`jnl`	Responsible computing during COVID-19 and beyond. Commun. ACM 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
2020	A*	`conf`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. NeurIPS Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	J	`jnl`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. CoRR Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	A*	`conf`	Doubly robust off-policy evaluation with shrinkage. ICML Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík
2020	A*	`conf`	Gradient descent follows the regularization path for general losses. COLT Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
2020	J	`jnl`	Gradient descent follows the regularization path for general losses. CoRR Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
2020	J	`jnl`	Oracle-efficient Online Learning and Auction Design. J. ACM Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2019	J	`jnl`	Doubly robust off-policy evaluation with shrinkage. CoRR Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík
2019	A*	`conf`	Fair Regression: Quantitative Definitions and Reduction-Based Algorithms. ICML Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu
2019	J	`jnl`	Fair Regression: Quantitative Definitions and Reduction-based Algorithms. CoRR Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu
2019	A*	`conf`	Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2019	A*	`conf`	Provably efficient RL with Rich Observations via Latent State Decoding. ICML Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford
2019	J	`jnl`	Provably efficient RL with Rich Observations via Latent State Decoding. CoRR Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford
2019	A*	`conf`	Reinforcement Learning with Convex Constraints. NeurIPS Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
2019	J	`jnl`	Reinforcement Learning with Convex Constraints. CoRR Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
2018	A*	`conf`	A Reductions Approach to Fair Classification. ICML Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
2018	J	`jnl`	A Reductions Approach to Fair Classification. CoRR Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
2018	A*	`conf`	Hierarchical Imitation and Reinforcement Learning. ICML Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III
2018	J	`jnl`	Hierarchical Imitation and Reinforcement Learning. CoRR Hoang Minh Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III
2018	J	`jnl`	Improving fairness in machine learning systems: What do industry practitioners need? CoRR Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2018	A*	`conf`	Practical Contextual Bandits with Regression Oracles. ICML Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
2018	J	`jnl`	Practical Contextual Bandits with Regression Oracles. CoRR Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
2017	—	`conf`	A Decomposition of Forecast Error in Prediction Markets. NIPS Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
2017	J	`jnl`	A Decomposition of Forecast Error in Prediction Markets. CoRR Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
2017	—	`conf`	Off-policy evaluation for slate recommendation. NIPS Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
2017	A*	`conf`	Optimal and Adaptive Off-policy Evaluation in Contextual Bandits. ICML Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudík
2017	A*	`conf`	Oracle-Efficient Online Learning and Auction Design. FOCS Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2017	Misc	`conf`	The group k-support norm for learning with structured sparsity. ICASSP Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui
2016	A*	`conf`	Arbitrage-Free Combinatorial Market Making via Integer Programming. EC Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan
2016	J	`jnl`	Arbitrage-Free Combinatorial Market Making via Integer Programming. CoRR Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan
2016	—	`conf`	Contextual semibandits via supervised learning oracles. NIPS Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík
2016	J	`jnl`	Off-policy evaluation for slate recommendation. CoRR Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
2016	J	`jnl`	Optimal and Adaptive Off-policy Evaluation in Contextual Bandits. CoRR Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudík
2016	J	`jnl`	Oracle-Efficient Learning and Auction Design. CoRR Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2015	A	`conf`	Budget Constraints in Prediction Markets. UAI Nikhil R. Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock
2015	J	`jnl`	Budget Constraints in Prediction Markets. CoRR Nikhil R. Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock
2015	A*	`conf`	Contextual Dueling Bandits. COLT Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
2015	J	`jnl`	Contextual Dueling Bandits. CoRR Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
2015	A*	`conf`	Convex Risk Minimization and Conditional Probability Estimation. COLT Matus Telgarsky, Miroslav Dudík
2015	J	`jnl`	Convex Risk Minimization and Conditional Probability Estimation. CoRR Matus Telgarsky, Miroslav Dudík, Robert E. Schapire
2015	J	`jnl`	Doubly Robust Policy Evaluation and Optimization. CoRR Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2015	J	`jnl`	Efficient Contextual Semi-Bandit Learning. CoRR Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík
2014	J	`jnl`	A reliable effective terascale linear learning system. J. Mach. Learn. Res. Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford
2014	A	`conf`	Market Making with Decreasing Utility for Information. UAI Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
2014	J	`jnl`	Market Making with Decreasing Utility for Information. CoRR Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
2014	A*	`conf`	Robust Multi-objective Learning with Mentor Feedback. COLT Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins
2013	A*	`conf`	A combinatorial prediction market for the U.S. elections. EC Miroslav Dudík, Sébastien Lahaie, David M. Pennock, David M. Rothschild
2013	J	`jnl`	Para-active learning. CoRR Alekh Agarwal, Léon Bottou, Miroslav Dudík, John Langford
2012	J	`jnl`	A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games CoRR Miroslav Dudík, Geoffrey J. Gordon
2012	A*	`conf`	A tractable combinatorial market maker using constraint generation. EC Miroslav Dudík, Sébastien Lahaie, David M. Pennock
2012	J	`jnl`	Contextual Bandit Learning with Predictable Rewards CoRR Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
2012	A	`conf`	Contextual Bandit Learning with Predictable Rewards. AISTATS Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
2012	J	`jnl`	First-Order Mixed Integer Linear Programming CoRR Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík
2012	—	`conf`	Identifying Culture and Leveraging Cultural Differences for Negotiation Agents. HICSS Brian D. Ziebart, Miroslav Dudík, Geoffrey J. Gordon, Katia P. Sycara, Wendi L. Adair, Jeanne M. Brett
2012	A*	`conf`	Large-scale image classification with trace-norm regularization. CVPR Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick
2012	A	`conf`	Lifted coordinate descent for learning with trace-norm regularization. AISTATS Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick
2012	J	`jnl`	Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits CoRR Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2012	A	`conf`	Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits. UAI Miroslav Dudík, Dumitru Erhan, John Langford, Lihong Li
2011	J	`jnl`	A Reliable Effective Terascale Linear Learning System CoRR Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford
2011	J	`jnl`	Doubly Robust Policy Evaluation and Learning CoRR Miroslav Dudík, John Langford, Lihong Li
2011	A*	`conf`	Doubly Robust Policy Evaluation and Learning. ICML Miroslav Dudík, John Langford, Lihong Li
2011	J	`jnl`	Efficient Optimal Learning for Contextual Bandits CoRR Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
2011	A	`conf`	Efficient Optimal Learning for Contextual Bandits. UAI Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
2011	A	`conf`	Maximizing revenue in symmetric resource allocation systems when user utilities exhibit diminishing returns. AAMAS Roie Zivan, Miroslav Dudík, Praveen Paruchuri, Katia P. Sycara
2011	A	`ed.`	Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011 AISTATS Geoffrey J. Gordon, David B. Dunson, Miroslav Dudík
2010	—	`conf`	Reducing Untruthful Manipulation in Envy-Free Pareto Optimal Resource Allocation. IAT Roie Zivan, Miroslav Dudík, Steven Okamoto, Katia P. Sycara
2009	A	`conf`	A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games. UAI Miroslav Dudík, Geoffrey J. Gordon
2009	A	`conf`	First-Order Mixed Integer Linear Programming. UAI Geoffrey J. Gordon, Sue Ann Hong, Miroslav Dudík
2008	—	`conf`	Generative and Discriminative Learning with Unknown Labeling Bias. NIPS Miroslav Dudík, Steven J. Phillips
2007	A*	`conf`	Hierarchical maximum entropy density estimation. ICML Miroslav Dudík, David M. Blei, Robert E. Schapire
2007	J	`jnl`	Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling. J. Mach. Learn. Res. Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
2007	—	`conf`	PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks. SemEval@ACL Jonathan D. Chang, Miroslav Dudík, David M. Blei
2006	A*	`conf`	Maximum Entropy Distribution Estimation with Generalized Regularization. COLT Miroslav Dudík, Robert E. Schapire
2005	—	`conf`	Correcting sample selection bias in maximum entropy density estimation. NIPS Miroslav Dudík, Robert E. Schapire, Steven J. Phillips
2004	A*	`conf`	A maximum entropy approach to species distribution modeling. ICML Steven J. Phillips, Miroslav Dudík, Robert E. Schapire
2004	A*	`conf`	Performance Guarantees for Regularized Maximum Entropy Density Estimation. COLT Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
2003	J	`jnl`	Reconstruction from subsequences. J. Comb. Theory A Miroslav Dudík, Leonard J. Schulman