Miroslav Dudı́k

Decision Sciences · Social Sciences

29h-index32.8kcitations96works0.42yr avg
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Research Topics

Advanced Bandit Algorithms Research(27), Machine Learning and Algorithms(26), Reinforcement Learning in Robotics(13), Species Distribution and Climate Change(13), Sports Analytics and Performance(13)

Publications96 total

On the Hardness of Bandit Learning
arXiv (Cornell University)·2025Open Access
SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation
arXiv (Cornell University)·2024Open Access
A structured regression approach for evaluating model performance across intersectional subgroups
2024· 2 citedOpen Access
A structured regression approach for evaluating model performance across intersectional subgroups
arXiv (Cornell University)·2024Open Access
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
2024
A Unified Model and Dimension for Interactive Estimation
arXiv (Cornell University)·2023Open Access
Fairlearn: Assessing and Improving Fairness of AI Systems
arXiv (Cornell University)·2023· 49 citedOpen Access
Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations
2022 ACM Conference on Fairness, Accountability, and Transparency·2022· 1 cited
Astral Space: Convex Analysis at Infinity
arXiv (Cornell University)·2022Open Access
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
arXiv (Cornell University)·2022· 7 citedOpen Access
Bayesian decision-making under misspecified priors with applications to meta-learning
arXiv (Cornell University)·2021· 2 citedOpen Access
Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations
2021Open Access
Bayesian decision-making under misspecified priors with applications to meta-learning
arXiv (Cornell University)·2021· 10 citedOpen Access
Responsible computing during COVID-19 and beyond
Communications of the ACM·2021· 2 cited
Log-time Prediction Markets for Interval Securities
2021· 1 citedOpen Access
Log-time Prediction Markets for Interval Securities
arXiv (Cornell University)·2021Open Access
Doubly robust off-policy evaluation with shrinkage
International Conference on Machine Learning·2020· 18 cited
Gradient descent follows the regularization path for general losses.
Conference on Learning Theory·2020· 12 cited
Gradient descent follows the regularization path for general losses
arXiv (Cornell University)·2020· 3 citedOpen Access
Constrained episodic reinforcement learning in concave-convex and knapsack settings
arXiv (Cornell University)·2020· 14 citedOpen Access
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Frequent Co-authors

Robert E. Schapire(17), Steven J. Phillips(11), John Langford(11), Alekh Agarwal(11), Akshay Krishnamurthy(5), Jane Elith(3), Daniel Hsu(3), Satyen Kale(3), Sobhan Miryoosefi(3), Kianté Brantley(3), Hal Daumé(3), Aleksandrs Slivkins(3), Catherine H. Graham(2), Robert P. Anderson(2), Simon Ferrier(2), John R. Leathwick(2), Anthony Lehmann(2), Lihong Li(2), Olivier Chapelle(2), Nikos Karampatziakis(2)