1 citations · 1 across the 2 of their papers we have counts for
5 papers
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS
Kaitlin Maile, Erwan Lecarpentier, Hervé Luga +1
Differentiable Architecture Search (DARTS) is a recent neural architecture search (NAS) method based on a differentiable relaxation. Due to its success, numerous variants analyzing…
Lipschitz Lifelong Reinforcement Learning
Erwan Lecarpentier, David Abel, Kavosh Asadi +3
We consider the problem of knowledge transfer when an agent is facing a series of Reinforcement Learning (RL) tasks. We introduce a novel metric between Markov Decision Processes (…
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning, Extended version
Erwan Lecarpentier, Emmanuel Rachelson
This work tackles the problem of robust zero-shot planning in non-stationary stochastic environments. We study Markov Decision Processes (MDPs) evolving over time and consider Mode…
Open Loop Execution of Tree-Search Algorithms, extended version
Erwan Lecarpentier, Guillaume Infantes, Charles Lesire +1
In the context of tree-search stochastic planning algorithms where a generative model is available, we consider on-line planning algorithms building trees in order to recommend an…
Empirical evaluation of a Q-Learning Algorithm for Model-free Autonomous Soaring
Erwan Lecarpentier, Sebastian Rapp, Marc Melo +1
Autonomous unpowered flight is a challenge for control and guidance systems: all the energy the aircraft might use during flight has to be harvested directly from the atmosphere. W…