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 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 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 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
Publication Provable RL with Exogenous Distractors via Multistep Inverse Dynamics Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford ICLR 2022 | October 2021
Publication From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan HCOMP 2021 | September 2021 Project
Publication Strategically Efficient Exploration in Competitive Multiagent Reinforcement Learning Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
Publication Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann 2021 International Conference on Machine Learning | July 2021 Source code available at: https://github.com/microsoft/NTT Video Github Project
