1 code implementation • 21 Feb 2024 • Paul Daoudi, Bogdan Robu, Christophe Prieur, Ludovic Dos Santos, Merwan Barlier
This paper addresses the problem of integrating local guide policies into a Reinforcement Learning agent.
1 code implementation • NeurIPS 2023 • Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy
Particle-based deep generative models, such as gradient flows and score-based diffusion models, have recently gained traction thanks to their striking performance.
no code implementations • NeurIPS 2019 • Igor Colin, Ludovic Dos Santos, Kevin Scaman
For smooth convex and non-convex objective functions, we provide matching lower and upper complexity bounds and show that a naive pipeline parallelization of Nesterov's accelerated gradient descent is optimal.
no code implementations • 12 Dec 2019 • George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux
In this paper, we show that a simple coloring scheme can improve, both theoretically and empirically, the expressive power of Message Passing Neural Networks(MPNNs).
no code implementations • NeurIPS 2020 • Kevin Scaman, Ludovic Dos Santos, Merwan Barlier, Igor Colin
This novel smoothing method is then used to improve first-order non-smooth optimization (both convex and non-convex) by allowing for a local exploration of the search space.
no code implementations • 29 Sep 2021 • Paul Daoudi, Merwan Barlier, Ludovic Dos Santos, Aladin Virmaux
We hence introduce Density Conservative Q-Learning (D-CQL), a batch-RL algorithm with strong theoretical guarantees that carefully penalizes the value function based on the amount of information collected in the state-action space.
no code implementations • 8 Sep 2023 • Veronika Shilova, Ludovic Dos Santos, Flavian vasile, Gaëtan Racic, Ugo Tanielian
In digital advertising, the selection of the optimal item (recommendation) and its best creative presentation (creative optimization) have traditionally been considered separate disciplines.
no code implementations • 24 Dec 2023 • Paul Daoudi, Christophe Prieur, Bogdan Robu, Merwan Barlier, Ludovic Dos Santos
In the few-shot framework, a limited number of transitions from the target environment are introduced to facilitate a more effective transfer.
no code implementations • 21 Feb 2024 • Paul Daoudi, Bojan Mavkov, Bogdan Robu, Christophe Prieur, Emmanuel Witrant, Merwan Barlier, Ludovic Dos Santos
This paper presents a learning-based control strategy for non-linear throttle valves with an asymmetric hysteresis, leading to a near-optimal controller without requiring any prior knowledge about the environment.