1 citations · 1 across the 6 of their papers we have counts for
6 papers
Symmetry-Aware Bayesian Optimization via Max Kernels
Anthony Bardou, Antoine Gonon, Aryan Ahadinia +1
Bayesian Optimization (BO) is a powerful framework for optimizing noisy, expensive-to-evaluate black-box functions. When the objective exhibits invariances under a group action, ex…
Asymptotic Performance of Time-Varying Bayesian Optimization
Anthony Bardou, Patrick Thiran
Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying black-box objective function that may be noisy and expensive to evaluate, but its exc…
Time-Varying Bayesian Optimization Without a Metronome
Anthony Bardou, Patrick Thiran
Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying, expensive, noisy black-box function . However, most of the asymptotic guarantees…
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
Anthony Bardou, Patrick Thiran, Giovanni Ranieri
Bayesian Optimization (BO) has proven to be very successful at optimizing a static, noisy, costly-to-evaluate black-box function . However, optimizi…
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
Anthony Bardou, Patrick Thiran, Thomas Begin
Bayesian Optimization (BO) is typically used to optimize an unknown function that is noisy and costly to evaluate, by exploiting an acquisition function that must be maximized…
INSPIRE: Distributed Bayesian Optimization for ImproviNg SPatIal REuse in Dense WLANs
Anthony Bardou, Thomas Begin
WLANs, which have overtaken wired networks to become the primary means of connecting devices to the Internet, are prone to performance issues due to the scarcity of space in the ra…