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ORCIDJoshua Romoff
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2020 – today
- 2024
[c13]Daniel Bairamian, Philippe Marcotte, Joshua Romoff, Gabriel Robert, Derek Nowrouzezahrai:
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play. AAMAS 2024: 114-122- [c12]Roger Creus Castanyer, Joshua Romoff, Glen Berseth:
Improving Intrinsic Exploration by Creating Stationary Objectives. ICLR 2024 - 2023
- [c11]Anthony Kobanda
, Valliappan C. A., Joshua Romoff, Ludovic Denoyer:
Learning Computational Efficient Bots with Costly Features. CoG 2023: 1-8 - [i17]Anthony Kobanda, Valliappan C. A., Joshua Romoff, Ludovic Denoyer:
Learning Computational Efficient Bots with Costly Features. CoRR abs/2308.09629 (2023) - [i16]Roger Creus Castanyer, Joshua Romoff, Glen Berseth:
Improving Intrinsic Exploration by Creating Stationary Objectives. CoRR abs/2310.18144 (2023) - [i15]Daniel Bairamian, Philippe Marcotte, Joshua Romoff, Gabriel Robert, Derek Nowrouzezahrai:
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play. CoRR abs/2311.17190 (2023) - 2022
- [c10]Julien Roy, Roger Girgis, Joshua Romoff, Pierre-Luc Bacon, Christopher J. Pal:
Direct Behavior Specification via Constrained Reinforcement Learning. ICML 2022: 18828-18843 - 2021
- [c9]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning? AAMAS 2021: 1082-1090 - [c8]Eloi Alonso, Maxim Peter, David Goumard, Joshua Romoff:
Deep Reinforcement Learning for Navigation in AAA Video Games. IJCAI 2021: 2133-2139 - [i14]Edward Beeching, Maxim Peter, Philippe Marcotte, Jilles Dibangoye, Olivier Simonin, Joshua Romoff, Christian Wolf:
Graph augmented Deep Reinforcement Learning in the GameRLand3D environment. CoRR abs/2112.11731 (2021) - [i13]Julien Roy, Roger Girgis, Joshua Romoff, Pierre-Luc Bacon, Christopher J. Pal:
Direct Behavior Specification via Constrained Reinforcement Learning. CoRR abs/2112.12228 (2021) - 2020
- [i12]Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau:
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR abs/2002.05651 (2020) - [i11]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? CoRR abs/2007.02786 (2020) - [i10]Eloi Alonso, Maxim Peter, David Goumard, Joshua Romoff:
Deep Reinforcement Learning for Navigation in AAA Video Games. CoRR abs/2011.04764 (2020)
2010 – 2019
- 2019
- [c7]Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, Joelle Pineau:
TarMAC: Targeted Multi-Agent Communication. ICML 2019: 1538-1546 - [c6]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill:
Separable value functions across time-scales. ICML 2019: 5468-5477 - [c5]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. NeurIPS 2019: 13299-13309 - [c4]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. UAI 2019: 422-432 - [i9]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau:
Separating value functions across time-scales. CoRR abs/1902.01883 (2019) - [i8]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. CoRR abs/1906.04585 (2019) - 2018
- [c3]Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL 2018: 674-699 - [c2]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) 2018 - [i7]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR abs/1805.03359 (2018) - [i6]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. CoRR abs/1806.02315 (2018) - [i5]Peter Henderson, Joshua Romoff, Joelle Pineau:
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. CoRR abs/1810.02525 (2018) - [i4]Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle Pineau:
TarMAC: Targeted Multi-Agent Communication. CoRR abs/1810.11187 (2018) - 2017
- [c1]Harm van Seijen, Mehdi Fatemi, Romain Laroche, Joshua Romoff, Tavian Barnes, Jeffrey Tsang:
Hybrid Reward Architecture for Reinforcement Learning. NIPS 2017: 5392-5402 - [i3]Romain Laroche, Mehdi Fatemi, Joshua Romoff, Harm van Seijen:
Multi-Advisor Reinforcement Learning. CoRR abs/1704.00756 (2017) - [i2]Harm van Seijen, Mehdi Fatemi, Joshua Romoff, Romain Laroche, Tavian Barnes, Jeffrey Tsang:
Hybrid Reward Architecture for Reinforcement Learning. CoRR abs/1706.04208 (2017) - 2016
- [i1]Harm van Seijen, Mehdi Fatemi, Joshua Romoff, Romain Laroche:
Improving Scalability of Reinforcement Learning by Separation of Concerns. CoRR abs/1612.05159 (2016)
Coauthor Index
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