Cédric Malherbe

According to our database, Cédric Malherbe authored at least 9 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Measures of diversity and space-filling designs for categorical data.

Cédric Malherbe, Emilio Domínguez-Sánchez, Merwan Barlier, Igor Colin, Haitham Bou-Ammar, Tom Diethe

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

Optimistic Tree Searches for Combinatorial Black-Box Optimization.

Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness.

Kevin Scaman, Cédric Malherbe, Ludovic Dos Santos

Proceedings of the International Conference on Machine Learning, 2022

Robustness in Multi-Objective Submodular Optimization: a Quantile Approach.

Cédric Malherbe, Kevin Scaman

Proceedings of the International Conference on Machine Learning, 2022

BOiLS: Bayesian Optimisation for Logic Synthesis.

Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2020

Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations.

Kevin Scaman, Cédric Malherbe

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017

Quelques contribtuions à l'optimisation globale. (Contributions to global optimization).

Cédric Malherbe

PhD thesis, 2017

Global optimization of Lipschitz functions.

Cédric Malherbe, Nicolas Vayatis

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

A ranking approach to global optimization.

Cédric Malherbe, Emile Contal, Nicolas Vayatis

Proceedings of the 33nd International Conference on Machine Learning, 2016