Publication Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints Amr Sharaf, Hal Daumé III, Renkun Ni FAccT 2022 | June 2022
Publication Provably sample-efficient RL with side information about latent dynamics Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire 2022 Neural Information Processing Systems | May 2022 Project
Publication Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu NAACL 2022 | May 2022
Publication REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach, Jennifer Wortman Vaughan FAccT 2022 | May 2022 Project
Publication Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni, Dylan Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford 2022 Conference on Learning Theory | May 2022
Publication Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford ICLR 2022 | April 2022
Publication Efficient and optimal algorithms for contextual dueling bandits under realizability Akshay Krishnamurthy, Aadirupa Saha International Conference on Algorithmic Learning Theory | April 2022
Publication Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits Suprovat Ghoshal, Aadirupa Saha AISTATS 2022 | February 2022
Publication Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna Wallach 25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2022) | February 2022
Publication Meta Learning MDPs with linear transition models Robert Müller, Aldo Pacchiano January 2022
