Groupe de lecture LIPN: Apprentissage et Optimisation

Jour, horaire, lieu: lundi de 14h à 15h en A303
Lien visio: https://bbb.lipn.univ-paris13.fr/b/ler-mou-dke-f0x
Lien calendrier (format ics): calendrier
Discussions: Canal Mattermost

2024/2025

Date	Article/Thème	Lecture animée par	Notes
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

AS 5 ET 2 FD 6 JLR 3 ML 3 NT 1 RWC 2 XH 1 YZ 6

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