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Didier Chételat
Didier Chételat
Senior Researcher, Huawei Noah's Ark lab
Preverjeni e-poštni naslov na huawei.com - Domača stran
Naslov
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Leto
Exact combinatorial optimization with graph convolutional neural networks
M Gasse, D Chételat, N Ferroni, L Charlin, A Lodi
Advances in Neural Information Processing Systems 32, 2019
4422019
Combinatorial optimization and reasoning with graph neural networks
Q Cappart, D Chételat, EB Khalil, A Lodi, C Morris, P Velickovic
J. Mach. Learn. Res. 24, 130:1-130:61, 2023
2772023
Ecole: A gym-like library for machine learning in combinatorial optimization solvers
A Prouvost, J Dumouchelle, L Scavuzzo, M Gasse, D Chételat, A Lodi
arXiv preprint arXiv:2011.06069, 2020
472020
Learning to Branch with Tree MDPs
L Scavuzzo, FY Chen, D Chételat, M Gasse, A Lodi, N Yorke-Smith, ...
Advances in Neural Information Processing Systems 35, 2022
292022
Improved multivariate normal mean estimation with unknown covariance when is greater than
D Chételat, MT Wells
242012
Optimal two-step prediction in regression
D Chételat, J Lederer, J Salmon
212017
Lookback for learning to branch
P Gupta, EB Khalil, D Chetélat, M Gasse, Y Bengio, A Lodi, MP Kumar
arXiv preprint arXiv:2206.14987, 2022
182022
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks
AG Labassi, D Chételat, A Lodi
Advances in Neural Information Processing Systems 35, 2022
162022
The machine learning for combinatorial optimization competition (ml4co): Results and insights
M Gasse, S Bowly, Q Cappart, J Charfreitag, L Charlin, D Chételat, ...
NeurIPS 2021 Competitions and Demonstrations Track, 220-231, 2022
162022
The middle-scale asymptotics of Wishart matrices
D Chételat, MT Wells
112019
Improved second order estimation in the singular multivariate normal model
D Chételat, MT Wells
Journal of Multivariate Analysis 147, 1-19, 2016
112016
Ecole: A library for learning inside milp solvers
A Prouvost, J Dumouchelle, M Gasse, D Chételat, A Lodi
arXiv preprint arXiv:2104.02828, 2021
62021
Combinatorial optimization and reasoning with graph neural networks, 2021
Q Cappart, D Chételat, E Khalil, A Lodi, C Morris, P Veličković
arXiv preprint arXiv:2102.09544, 0
6
Exploring the power of graph neural networks in solving linear optimization problems
C Qian, D Chételat, C Morris
arXiv preprint arXiv:2310.10603, 2023
42023
Noise estimation in the spiked covariance model
D Chételat, MT Wells
arXiv preprint arXiv:1408.6440, 2014
42014
Continuous cutting plane algorithms in integer programming
D Chételat, A Lodi
Operations Research Letters 51 (4), 439-445, 2023
22023
Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems
R Sterzinger, J Poland, MB Paulus, D Chételat
2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), 1-5, 2023
2023
Deep Unsupervised Anomaly Detection in High-Frequency Markets
C Poutré, D Chételat, M Morales
Available at SSRN, 2023
2023
Change Point Detection by Cross-Entropy Maximization
A Serre, D Chételat, A Lodi
arXiv preprint arXiv:2009.01358, 2020
2020
On the domain of attraction of a Tracy–Widom law with applications to testing multiple largest roots
D Chételat, R Narayanan, MT Wells
Journal of Multivariate Analysis 165, 132-142, 2018
2018
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