Emmanuel Rachelson

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 47

Top Topics

Combinatorial Optimization

Markov Decision Process

Variational Inference

Reinforcement Learning

Top Venues

Comput. Oper. Res.

Publications

Paul-Antoine Le Tolguenec, Emmanuel Rachelson, Yann Besse, Dennis Wilson
Summary of "Curiosity creates Diversity in Policy Search". GECCO Companion (2024)
Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson
Time-Constrained Robust MDPs. CoRR (2024)
Paul Templier, Emmanuel Rachelson, Antoine Cully, Dennis G. Wilson
Genetic Drift Regularization: On Preventing Actor Injection from Breaking Evolution Strategies. CEC (2024)
Pierre Clavier, Emmanuel Rachelson, Erwan Le Pennec, Matthieu Geist
Bootstrapping Expectiles in Reinforcement Learning. CoRR (2024)
Paul-Antoine Le Tolguenec, Yann Besse, Florent Teichteil-Königsbuch, Dennis G. Wilson, Emmanuel Rachelson
Exploration by Learning Diverse Skills through Successor State Measures. CoRR (2024)
Paul Templier, Luca Grillotti, Emmanuel Rachelson, Dennis Wilson, Antoine Cully
Quality with Just Enough Diversity in Evolutionary Policy Search. GECCO (2024)
Mehdi Zouitine, Ahmad Berjaoui, Agnès Lagnoux, Clément Pellegrini, Emmanuel Rachelson
Learning Heuristics for Combinatorial Optimization Problems on K-Partite Hypergraphs. CPAIOR (2) (2024)
Paul Templier, Luca Grillotti, Emmanuel Rachelson, Dennis G. Wilson, Antoine Cully
Quality with Just Enough Diversity in Evolutionary Policy Search. CoRR (2024)
Paul Templier, Emmanuel Rachelson, Antoine Cully, Dennis G. Wilson
Genetic Drift Regularization: on preventing Actor Injection from breaking Evolution Strategies. CoRR (2024)
Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson
RRLS : Robust Reinforcement Learning Suite. CoRR (2024)
David Bertoin, Emmanuel Rachelson
Disentanglement by Cyclic Reconstruction. IEEE Trans. Neural Networks Learn. Syst. 35 (5) (2024)
Paul-Antoine Le Tolguenec, Emmanuel Rachelson, Yann Besse, Dennis G. Wilson
Curiosity Creates Diversity in Policy Search. ACM Trans. Evol. Learn. Optim. 3 (3) (2023)
François Lamothe, Emmanuel Rachelson, Alain Haït, Cédric Baudoin, Jean-Baptiste Dupe
Randomized rounding algorithms for large scale unsplittable flow problems. CoRR (2023)
François Lamothe, Emmanuel Rachelson, Alain Haït, Cédric Baudoin, Jean-Baptiste Dupe
Dynamic unsplittable flows with path-change penalties: New formulations and solution schemes for large instances. Comput. Oper. Res. 152 (2023)
Valentin Guillet, Dennis G. Wilson, Carlos Aguilar Melchor, Emmanuel Rachelson
Neural Distillation as a State Representation Bottleneck in Reinforcement Learning. CoRR (2022)
Thibault Lahire, Matthieu Geist, Emmanuel Rachelson
Large Batch Experience Replay. ICML (2022)
David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson
Look where you look! Saliency-guided Q-networks for visual RL tasks. CoRR (2022)
Valentin Guillet, Dennis Wilson, Carlos Aguilar Melchor, Emmanuel Rachelson
On Neural Consolidation for Transfer in Reinforcement Learning. SSCI (2022)
Paul-Antoine Le Tolguenec, Emmanuel Rachelson, Yann Besse, Dennis G. Wilson
Curiosity creates Diversity in Policy Search. CoRR (2022)
Kaitlin Maile, Emmanuel Rachelson, Hervé Luga, Dennis George Wilson
When, where, and how to add new neurons to ANNs. AutoML (2022)
Valentin Guillet, Dennis G. Wilson, Carlos Aguilar Melchor, Emmanuel Rachelson
On Neural Consolidation for Transfer in Reinforcement Learning. CoRR (2022)
David Bertoin, Emmanuel Rachelson
Local Feature Swapping for Generalization in Reinforcement Learning. ICLR (2022)
Erwan Lecarpentier, Paul Templier, Emmanuel Rachelson, Dennis G. Wilson
LUCIE: an evaluation and selection method for stochastic problems. GECCO (2022)
Kaitlin Maile, Emmanuel Rachelson, Hervé Luga, Dennis G. Wilson
When, where, and how to add new neurons to ANNs. CoRR (2022)
David Bertoin, Emmanuel Rachelson
Local Feature Swapping for Generalization in Reinforcement Learning. CoRR (2022)
Valentin Guillet, Dennis George Wilson, Emmanuel Rachelson
Neural Distillation as a State Representation Bottleneck in Reinforcement Learning. CoLLAs (2022)
David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning. NeurIPS (2022)
Sana Ikli, Catherine Mancel, Marcel Mongeau, Xavier Olive, Emmanuel Rachelson
The aircraft runway scheduling problem: A survey. Comput. Oper. Res. 132 (2021)
Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
Lipschitz Lifelong Reinforcement Learning. AAAI (2021)
David Bertoin, Emmanuel Rachelson
Disentanglement by Cyclic Reconstruction. CoRR (2021)
Paul Templier, Emmanuel Rachelson, Dennis G. Wilson
A geometric encoding for neural network evolution. GECCO (2021)
Thibault Lahire, Matthieu Geist, Emmanuel Rachelson
Large Batch Experience Replay. CoRR (2021)
François Lamothe, Emmanuel Rachelson, Alain Haït, Cédric Baudoin, Jean-Baptiste Dupe
Randomized rounding algorithms for large scale unsplittable flow problems. J. Heuristics 27 (6) (2021)
Andrea Lodi, Luca Mossina, Emmanuel Rachelson
Learning to handle parameter perturbations in Combinatorial Optimization: An application to facility location. EURO J. Transp. Logist. 9 (4) (2020)
Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
Lipschitz Lifelong Reinforcement Learning. CoRR (2020)
Andrea Lodi, Luca Mossina, Emmanuel Rachelson
Learning to Handle Parameter Perturbations in Combinatorial Optimization: an Application to Facility Location. CoRR (2019)
Erwan Lecarpentier, Emmanuel Rachelson
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning. NeurIPS (2019)
Erwan Lecarpentier, Emmanuel Rachelson
Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning. CoRR (2019)
Luca Mossina, Emmanuel Rachelson, Daniel Delahaye
Multi-label Classification for the Generation of Sub-problems in Time-constrained Combinatorial Optimization. ICORES (2019)
Luca Mossina, Emmanuel Rachelson, Daniel Delahaye
A Reinforcement Learning Perspective on the Optimal Control of Mutation Probabilities for the (1+1) Evolutionary Algorithm: First Results on the OneMax Problem. CoRR (2019)
Erwan Lecarpentier, Guillaume Infantes, Charles Lesire, Emmanuel Rachelson
Open Loop Execution of Tree-Search Algorithms. JFPDA (2018)
Erwan Lecarpentier, Guillaume Infantes, Charles Lesire, Emmanuel Rachelson
Open Loop Execution of Tree-Search Algorithms. CoRR (2018)
Erwan Lecarpentier, Guillaume Infantes, Charles Lesire, Emmanuel Rachelson
Open Loop Execution of Tree-Search Algorithms. IJCAI (2018)
Luca Mossina, Emmanuel Rachelson
Naive Bayes Classification for Subset Selection. CoRR (2017)
Erwan Lecarpentier, Sebastian Rapp, Marc Melo, Emmanuel Rachelson
Empirical evaluation of a Q-Learning Algorithm for Model-free Autonomous Soaring. CoRR (2017)
Ankit Chiplunkar, Emmanuel Rachelson, Michele Colombo, Joseph Morlier
Sparse Physics-based Gaussian Process for Multi-output Regression using Variational Inference. ICPRAM (2016)
Ankit Chiplunkar, Emmanuel Rachelson, Michele Colombo, Joseph Morlier
Approximate Inference in Related Multi-output Gaussian Process Regression. ICPRAM (Revised Selected Papers) (2016)
Nicolas Regis, Frédéric Dehais, Emmanuel Rachelson, Charles Thooris, Sergio Pizziol, Mickaël Causse, Catherine Tessier
Formal Detection of Attentional Tunneling in Human Operator-Automation Interactions. IEEE Trans. Hum. Mach. Syst. 44 (3) (2014)
Emmanuel Rachelson, François Schnitzler, Louis Wehenkel, Damien Ernst
Optimal Sample Selection for Batch-mode Reinforcement Learning. ICAART (1) (2011)
Emmanuel Rachelson, Michail G. Lagoudakis
On the locality of action domination in sequential decision making. ISAIM (2010)
Emmanuel Rachelson, Ala Ben Abbes, Sebastien Diemer
Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning. ICTAI (2) (2010)
Emmanuel Rachelson, Patrick Fabiani, Frédérick Garcia
TiMDPpoly: An Improved Method for Solving Time-Dependent MDPs. ICTAI (2009)
Emmanuel Rachelson, Frédérick Garcia, Patrick Fabiani
Extending the Bellman equation for MDPs to continuous actions and cont. time in the discounted case. ISAIM (2008)
Emmanuel Rachelson, Gauthier Quesnel, Frédérick Garcia, Patrick Fabiani
A Simulation-based Approach for Solving Generalized Semi-Markov Decision Processes. ECAI (2008)