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ORCIDCédric Malherbe
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2020 – today
- 2024
[c8]Cédric Malherbe, Emilio Domínguez-Sánchez, Merwan Barlier, Igor Colin, Haitham Bou-Ammar, Tom Diethe:
Measures of diversity and space-filling designs for categorical data. ICML 2024- 2022
- [c7]Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar:
BOiLS: Bayesian Optimisation for Logic Synthesis. DATE 2022: 1193-1196 - [c6]Cédric Malherbe, Kevin Scaman:
Robustness in Multi-Objective Submodular Optimization: a Quantile Approach. ICML 2022: 14871-14886 - [c5]Kevin Scaman, Cédric Malherbe, Ludovic Dos Santos:
Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness. ICML 2022: 19310-19327 - [c4]Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang:
Optimistic Tree Searches for Combinatorial Black-Box Optimization. NeurIPS 2022 - 2021
- [i1]Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan
, Jun Wang, Haitham Bou-Ammar:
BOiLS: Bayesian Optimisation for Logic Synthesis. CoRR abs/2111.06178 (2021) - 2020
- [c3]Kevin Scaman, Cédric Malherbe:
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations. NeurIPS 2020
2010 – 2019
- 2017
- [b1]Cédric Malherbe:
Quelques contribtuions à l'optimisation globale. (Contributions to global optimization). École normale supérieure Paris-Saclay, Cachan, France, 2017 - [c2]Cédric Malherbe, Nicolas Vayatis:
Global optimization of Lipschitz functions. ICML 2017: 2314-2323 - 2016
- [c1]Cédric Malherbe, Emile Contal, Nicolas Vayatis:
A ranking approach to global optimization. ICML 2016: 1539-1547
Coauthor Index
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