Groupe de lecture LIPN: Apprentissage et Optimisation

Table of Contents

leroux-at-lipn.fr

Organisation

Jour, horaire, lieu
voir calendrier
Lien visio
https://bbb.lipn.univ-paris13.fr/b/ler-mou-dke-f0x
Lien calendrier (format ics)
calendrier
Discussions
Canal Mattermost

2025/2026

Date Article/Thème Lecture animée par Notes
11/12/25 09:30 Learning with Fenchel-Young Losses 5/n Nadi Tomeh B107
04/12/25 09:30 Learning with Fenchel-Young Losses 4/n Nadi Tomeh B107
27/11/25 09:30 Learning with Fenchel-Young Losses 3/n Joseph Le Roux A303
20/11/25 09:30 Learning with Fenchel-Young Losses 2/n Joseph Le Roux A303
06/11/25 Learning with Fenchel-Young Losses 1/n Joseph Le Roux A303

2024/2025

Date Article/Thème Lecture animée par Notes
16/12/24 Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? Mathieu Lacroix B107
18/11/24 A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Alexandre Schulz  
04/11/24 LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Francesco Demelas  
07/10/24 A New Branch-and-Bound Pruning Framework for L0-Regularized Problems Yue Zhang  
23/09/24 Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing Alexandre Schulz  

2023/2024

Date Article/Thème Lecture animée par Notes
17/06/24 Adaptive Stabilization Based on Machine Learning for Column Generation Francesco Demelas  
14/05/24 ML/OPT: The Voice of Optimization Roberto Wolfler-Calvo à 12h30 en B107
23/04/24 ML/OPT: DOGE-Train: Discrete Optimization on GPU with End-to-end Training Mathieu Lacroix présentation
25/03/24 A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity Yue Zhang  
05/02/24 + 04/03/24 Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method Alexandre Schulz  
22/01/24 DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization Joseph Le Roux présentation
08/01/24 Learning to learn by gradient descent by gradient descent Francesco Demelas présentation
13/11/23 Multi-Task Learning as Multi-Objective Optimization Yue Zhang  
09/10/23 Generic Methods for Optimization-Based Modeling Alexandre Schulz  
18/09/23 Fast as CHITA: Neural Network Pruning with Combinatorial Optimization Yue Zhang présentation
11/09/23 End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization Francesco Demelas présentation

2022/2023

Date Article/Thème Lecture animée par Notes
25/05/23 NLP/ML/CO: a case study Nadi Tomeh  
17/05/23 Fast Continuous and Integer L-shaped Heuristics Through Supervised Learning Francesco Demelas présentation
11/05/23 Constrained Discrete Black-Box Optimization using Mixed-Integer Programming Alexandre Schulz présentation
19/04/23 Reinforcement learning with combinatorial actions: An application to vehicle routing Emiliano Traversi en B107
13/04/23 Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation Francesco Demelas  
29/03/23 Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model Mathieu Lacroix présentation
16/03/23 Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization Yue Zhang  
09/03/23 Deep ADMM-Net for Compressive Sensing MRI Joseph Le Roux  
09/02/23 A Deep Reinforcement Learning Framework For Column Generation Emiliano Traversi  
18/01/23 COIL: A Deep Architecture for Column Generation Mathieu Lacroix présentation
11/01/23 UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning Francesco Demelas présentation
04/01/23 Strong mixed-integer programming formulations for trained neural networks Yue Zhang  
07/12/22 Machine-learning-based arc selection for constrained shortest path problems in column generation Roberto Wolfler-Calvo  
09/11/22 Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Joseph Le Roux présentation
03/10/22 Solving Mixed Integer Programs Using Neural Networks Xin He  
26/09/22 MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers Alexandre Schulz présentation
19/09/22 Learning with Combinatorial Optimization Layers: a Probabilistic Approach Francesco Demelas présentation

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