Daniel J. Mankowitz
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
5
Active years
2014–2024
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICML | Nash Learning from Human Feedback. | Rmi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Cme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot |
| 2023 | ICML | Transformers Meet Directed Graphs. | Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Gnnemann, Cosmin Paduraru |
| 2022 | ICLR | COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. | Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez |
| 2021 | CoRL | A Constrained Multi-Objective Reinforcement Learning Framework. | Sandy H. Huang, Abbas Abdolmaleki, Giulia Vezzani, Philemon Brakel, Daniel J. Mankowitz, Michael Neunert, Steven Bohez, Yuval Tassa, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell |
| 2021 | ICLR | Balancing Constraints and Rewards with Meta-Gradient D4PG. | Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann |
| 2021 | ICLR | Discovering a set of policies for the worst case reward. | Tom Zahavy, Andr Barreto, Daniel J. Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Singh |
| 2020 | ICLR | Robust Reinforcement Learning for Continuous Control with Model Misspecification. | Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller |
| 2019 | ICLR | Universal Successor Features Approximators. | Diana Borsa, Andr Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Rmi Munos, David Silver, Tom Schaul |
| 2019 | ICLR | Reward Constrained Policy Optimization. | Chen Tessler, Daniel J. Mankowitz, Shie Mannor |
| 2019 | UAI | A Bayesian Approach to Robust Reinforcement Learning. | Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor |
| 2018 | AAAI | Learning Robust Options. | Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor |
| 2018 | ICLR | Learning How Not to Act in Text-based Games. | Matan Haroush, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor |
| 2018 | ICML | Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. | Andr Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zdek, Rmi Munos |
| 2018 | UAI | Soft-Robust Actor-Critic Policy-Gradient. | Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor |
| 2017 | AAAI | A Deep Hierarchical Approach to Lifelong Learning in Minecraft. | Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor |
| 2015 | AAAI | Learning When to Switch between Skills in a High Dimensional Domain. | Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor |
| 2014 | ICML | Time-Regularized Interrupting Options (TRIO). | Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor |