Ray Jiang - RankMe

21 papers A* 5A 1C 1Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals
2023	A*	`conf`	Human-level Atari 200x faster. ICLR Steven Kapturowski, Victor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt, Charles Blundell, Adrià Puigdomènech Badia
2023	J	`jnl`	Scaling Goal-based Exploration via Pruning Proto-goals. CoRR Akhil Bagaria, Ray Jiang, Ramana Kumar, Tom Schaul
2022	J	`jnl`	Human-level Atari 200x faster. CoRR Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt, Charles Blundell, Adrià Puigdomènech Badia
2022	A*	`conf`	Learning Expected Emphatic Traces for Deep RL. AAAI Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
2021	A*	`conf`	Emphatic Algorithms for Deep Reinforcement Learning. ICML Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
2021	J	`jnl`	Emphatic Algorithms for Deep Reinforcement Learning. CoRR Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
2021	J	`jnl`	Learning Expected Emphatic Traces for Deep RL. CoRR Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
2020	A*	`conf`	A General Approach to Fairness with Optimal Transport. AAAI Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides
2020	J	`jnl`	Causally Correct Partial Models for Reinforcement Learning. CoRR Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing
2020	—	`conf`	Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. EMNLP (Findings) Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli
2019	—	`conf`	Beyond Greedy Ranking: Slate Optimization via List-CVAE. ICLR (Poster) Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy A. Mann, Danilo J. Rezende
2019	C	`conf`	Degenerate Feedback Loops in Recommender Systems. AIES Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
2019	J	`jnl`	Degenerate Feedback Loops in Recommender Systems. CoRR Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
2019	A*	`conf`	Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems. ICML Timothy A. Mann, Sven Gowal, András György, Huiyi Hu, Ray Jiang, Balaji Lakshminarayanan, Prav Srinivasan
2019	J	`jnl`	Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. CoRR Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli
2019	A	`conf`	Wasserstein Fair Classification. UAI Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
2019	J	`jnl`	Wasserstein Fair Classification. CoRR Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
2018	—	`conf`	Delayed learning, multi-objective optimization, and whole slate generation in recommender systems. DLRS@RecSys Ray Jiang
2018	J	`jnl`	Learning from Delayed Outcomes with Intermediate Observations. CoRR Timothy A. Mann, Sven Gowal, Ray Jiang, Huiyi Hu, Balaji Lakshminarayanan, András György
2018	J	`jnl`	Optimizing Slate Recommendations via Slate-CVAE. CoRR Ray Jiang, Sven Gowal, Timothy A. Mann, Danilo J. Rezende