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Influence branching for learning to solve mixed-integer programs online

Published in MIP Workshop, 2023

On the occasion of the 20th Mixed Integer Program Workshop Computational Competition, this work introduces a new approach for learning to solve MIPs online.

Recommended citation: Strang, P., Alès, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., (2023). Influence branching for learning to solve mixed-integer programs online. Mixed Integer Programming Workshop.

A Markov decision process for variable selection in Branch & Bound

Published in Neural Information Processing Systems (NeurIPS), 2025

In this work, we introduce BBMDP, a principled vanilla MDP formulation for variable selection in B&B, allowing to leverage a broad range of RL algorithms for the purpose of learning optimal B&B heuristics.

Recommended citation: Strang, P., Ales, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., 2025. A Markov Decision Process for Variable Selection in Branch & Bound. Presented at the The Thirty-ninth Annual Conference on Neural Information Processing Systems.

Planning in Branch-and-Bound: Model-based Reinforcement Learning for Exact Combinatorial Optimization

Published in AAAI Conference on Artificial Intelligence (AAAI), 2026

We introduce PlanB&B, a model-based reinforcement learning agent that learns an internal model of Branch & Bound dynamics to derive improved branching strategies for variable selection in B&B.

Recommended citation: Strang, P., Alès, Z., Bissuel, C., Juan, O., Kedad-Sidhoum, S., Rachelson, E., (2026). Planning in Branch-and-Bound: Model-based Reinforcement Learning for Exact Combinatorial Optimization. Proceedings of the Fortieth AAAI Conference on Artificial Intelligence..

Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.

Introduction to Reinforcement Learning

Internal training program, EDF R&D, 2024

In charge of an internal reinforcement learning training program open to researchers and engineers at EDF R&D. The program covers fundamental concepts, algorithms, and practical applications of reinforcement learning in industrial settings. The course follows Emmanuel Rachelson’s MVA class material.

Introduction to Linear and Mixed-Integer Programming

Master 2 course, Conservatoire des arts et métiers, 2025

In charge of introductory courses on linear programming and mixed-integer linear programming at MPRO, one of Europe’s leading research master’s programs in operations research. Additionally, served as teaching assistant for the Metaheuristics class.