Cédric Malherbe
Research Engineer at Huawei
Contact Details
E-mail: cedric.malherb [at] gmail.com
Currently interested in Symbolic Regression / Combinatorial Optimization / Deep Learning
Publications
Optimistic Tree Search Strategies for Combinatorial Optimization
Cedric Malherbe, Antoine Grosnit, Jun Wang, Haitham Bou-Ammar (NeurIPS 2022)
Robustness in Submodular Optimization: a Quantile Approach
Cedric Malherbe and Kevin Scaman (ICML 2022)
Kevin Scaman, Cedric Malherbe, Ludovic Dos Santos (ICML 2022)
Learning efficient black-box solvers and application to hyperparameter tuning
Sofian Chaybouti, Ludovic Dos Santos, Aladin Virmaux, Cédric Malherbe (NeurIPS workshop on Meta-Learning 2022)
Antoine Grosnit*, Cedric Malherbe*, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou Ammar (DATE 2021)
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations
Kevin Scaman and Cedric Malherbe (NeurIPS 2020)
Cédric Malherbe and Nicolas Vayatis (ICML 2017)
Cédric Malherbe and Nicolas Vayatis (ICML 2016)
Emile Contal, Cédric Malherbe and Nicolas Vayatis (NIPS 2015 Workshop on Bayesian Optimization)
Journal Versions
Cédric Malherbe and Nicolas Vayatis - Submitted to JMLR
Cédric Malherbe and Nicolas Vayatis - Submitted to JMLR
Other
Cédric Malherbe
Teaching
Introduction to statistical learning, Fall 2016, Master MVA, ENS Cachan
Statistiques/Apprentissage, Fall 2016, Ecole Centrale Paris
Apprentissage Statistique, Fall 2016, M1 ENS Cachan
Data/Apprentissage, Fall 2016, M2 UVSQ
Other
Open-source library for lipschitz optimization (implementation of my algorithms in C++)
Open-source library for nonlinear optimization
Open-source library for bayesian optimization
Open-source library for covariance matrix adaptation evolution strategy
Convert your photos into art using deep neural networks