2 citations · 2 across the 5 of their papers we have counts for
6 papers
STREGO: A Scalable Implementation of a Trust-Region Framework for Noisy Bayesian Optimization
Youssef Diouane, Issmail El Hallaoui, Meisseme Kadri +1
TREGO, a trust-region Bayesian optimization (BO) method for expensive blackbox problems, has convergence guarantees, but only for exact function values. In high dimension, its perf…
Benchmarking Bilevel Derivative-Free Optimization Algorithms
Charles Audet, Valentin Dijon, Youssef Diouane
Bilevel optimization involves an upper-level and a lower-level decision maker. The lower-level optimization problem is nested within the constraints of the upper-level one. A point…
Online Sketched Newton-Raphson
Jean-Luc Lupien, Yuen-Man Pun, Youssef Diouane +2
In online convex optimization (OCO), a decision-maker is confronted with an unknown environment and seeks to play an optimal sequence of decisions on a short time-scale using only…
Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
Amir Ali Farzin, Yuen Man Pun, Philipp Braun +3
This study explores the performance of the random Gaussian smoothing Zeroth-Order ExtraGradient (ZO-EG) scheme considering \Af{deterministic} min-max optimisation problems with pos…
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning
Youssef Diouane, Aurelien Lucchi, Vihang Patil
Evolutionary strategies have recently been shown to achieve competing levels of performance for complex optimization problems in reinforcement learning. In such problems, one often…
Direct-Search for a Class of Stochastic Min-Max Problems
Sotiris Anagnostidis, Aurelien Lucchi, Youssef Diouane
Recent applications in machine learning have renewed the interest of the community in min-max optimization problems. While gradient-based optimization methods are widely used to so…