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
Publication A Human-Centered Agenda for Intelligible Machine Learning Jennifer Wortman Vaughan, Hanna Wallach In Machines We Trust: Perspectives on Dependable AI | Published by MIT Press | 2021 Project
Publication GAM Changer: Editing Generalized Additive Models with Interactive Visualization Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana 2021 Neural Information Processing Systems | December 2021 Github
Publication Summarize with Caution: Comparing Global Feature Attributions Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021 Project
Publication Datasheets for Datasets Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford Communications of the ACM | December 2021, Vol 64(12): pp. 86-92 Project Project
Publication Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang, Kaixuan Huang, Sham Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang NeurIPS 2021 | December 2021
Publication Towards an Understanding of Default Policies in Multitask Policy Optimization Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano AISTATS 2022 | November 2021
