Ahmed Touati

According to our database, Ahmed Touati authored at least 25 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Simple Ingredients for Offline Reinforcement Learning.

Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati

CoRR, 2024

2023

Score Models for Offline Goal-Conditioned Reinforcement Learning.

Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum

CoRR, 2023

A State Representation for Diminishing Rewards.

Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Does Zero-Shot Reinforcement Learning Exist?

Ahmed Touati, Jérémy Rapin, Yann Ollivier

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees.

Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learning One Representation to Optimize All Rewards.

Ahmed Touati, Yann Ollivier

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?

Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Efficient Learning in Non-Stationary Linear Markov Decision Processes.

Ahmed Touati, Pascal Vincent

CoRR, 2020

Maximum Reward Formulation In Reinforcement Learning.

Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Sahir, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E. Taylor, Sarath Chandar

CoRR, 2020

Sharp Analysis of Smoothed Bellman Error Embedding.

Ahmed Touati, Pascal Vincent

CoRR, 2020

TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau

CoRR, 2020

Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces.

Ahmed Touati, Adrien Ali Taïga, Marc G. Bellemare

CoRR, 2020

Stable Policy Optimization via Off-Policy Divergence Regularization.

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

SVRG for Policy Evaluation with Fewer Gradient Evaluations.

Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Stochastic Neural Network with Kronecker Flow.

Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future.

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

CoRR, 2019

Separating value functions across time-scales.

Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau

CoRR, 2019

Randomized Value Functions via Multiplicative Normalizing Flows.

Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Separable value functions across time-scales.

Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill

Proceedings of the 36th International Conference on Machine Learning, 2019

Modeling the Long Term Future in Model-Based Reinforcement Learning.

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Convergent TREE BACKUP and RETRACE with Function Approximation.

Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent

Proceedings of the 35th International Conference on Machine Learning, 2018

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Learnable Explicit Density for Continuous Latent Space and Variational Inference.

Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron C. Courville

CoRR, 2017

Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien

CoRR, 2017

2014

Real-time privacy-preserving model-based estimation of traffic flows.

Jerome Le Ny, Ahmed Touati, George J. Pappas

Proceedings of the ACM/IEEE International Conference on Cyber-Physical Systems, 2014