Jiang, Ray

8 publications

ICLR 2023 Human-Level Atari 200x Faster Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt, Charles Blundell, Adria Puigdomenech Badia

AAAI 2022 Learning Expected Emphatic Traces for Deep RL Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt

ICML 2021 Emphatic Algorithms for Deep Reinforcement Learning Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado Van Hasselt

NeurIPSW 2021 StarCraft II Unplugged: Large Scale Offline Reinforcement Learning Michael Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Caglar Gulcehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Konrad Zolna, Richard Powell, Julian Schrittwieser, David Choi, Petko Georgiev, Daniel Kenji Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aaron van den Oord, Wojciech M. Czarnecki, Nando de Freitas, Oriol Vinyals

AAAI 2020 A General Approach to Fairness with Optimal Transport Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides

ICLR 2019 Beyond Greedy Ranking: Slate Optimization via List-CVAE Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy Mann, Danilo J. Rezende

ICML 2019 Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems Timothy Arthur Mann, Sven Gowal, Andras Gyorgy, Huiyi Hu, Ray Jiang, Balaji Lakshminarayanan, Prav Srinivasan

UAI 2019 Wasserstein Fair Classification Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa