174 citations
- Institut national de recherche en sciences et technologies du numériqueFR146 papers
- Université de LilleFR64 papers
- Centre National de la Recherche ScientifiqueFR49 papers
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR41 papers
- Centre de Recherche en InformatiqueFR30 papers
- École Centrale de LilleFR19 papers
- Laboratoire d'Informatique Fondamentale de LilleFR18 papers
- Laboratoire Paul PainlevéFR17 papers
- University College LondonGB16 papers
- Université Libre de BruxellesBE11 papers
- Université Paris-SaclayFR11 papers
- University of LondonGB9 papers
30 papers · 1 filter
Learning via Surrogate PAC-Bayes
Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj
PAC-Bayes learning is a comprehensive setting for (i) studying the generalisation ability of learning algorithms and (ii) deriving new learning algorithms by optimising a generalis…
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits
Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu
High dimensional sparse linear bandits serve as an efficient model for sequential decision-making problems (e.g. personalized medicine), where high dimensional features (e.g. genom…
Closed-form Filtering for Non-linear Systems
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj +1
Sequential Bayesian Filtering aims to estimate the current state distribution of a Hidden Markov Model, given the past observations. The problem is well-known to be intractable for…
A note on regularised NTK dynamics with an application to PAC-Bayesian training
Eugenio Clerico, Benjamin Guedj
We establish explicit dynamics for neural networks whose training objective has a regularising term that constrains the parameters to remain close to their initial value. This keep…
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption
Shubhada Agrawal, Timothée Mathieu, Debabrota Basu +1
We investigate the regret-minimisation problem in a multi-armed bandit setting with arbitrary corruptions. Similar to the classical setup, the agent receives rewards generated inde…
Price of Safety in Linear Best Arm Identification
Xuedong Shang, Igor Colin, Merwan Barlier +1
We introduce the safe best-arm identification framework with linear feedback, where the agent is subject to some stage-wise safety constraint that linearly depends on an unknown pa…