174 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- 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
17 papers · 1 filter
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…
Multi-Objective Reinforcement Learning Based on Decomposition: A Taxonomy and Framework
Florian Felten, El-Ghazali Talbi, Grégoire Danoy
Multi-objective reinforcement learning (MORL) extends traditional RL by seeking policies making different compromises among conflicting objectives. The recent surge of interest in…
Hyperparameter Optimization for Multi-Objective Reinforcement Learning
Florian Felten, Daniel Gareev, El-Ghazali Talbi +1
Reinforcement learning (RL) has emerged as a powerful approach for tackling complex problems. The recent introduction of multi-objective reinforcement learning (MORL) has further e…
Comparing Comparators in Generalization Bounds
Fredrik Hellström, Benjamin Guedj
We derive generic information-theoretic and PAC-Bayesian generalization bounds involving an arbitrary convex comparator function, which measures the discrepancy between the trainin…
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…
While Loops in Coq
David Nowak, Vlad Rusu
While loops are present in virtually all imperative programming languages. They are important both for practical reasons (performing a number of iterations not known in advance) an…
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…
Scalable Learning of Intrusion Responses through Recursive Decomposition
Kim Hammar, Rolf Stadler
We study automated intrusion response for an IT infrastructure and formulate the interaction between an attacker and a defender as a partially observed stochastic game. To solve th…
Concentrated Differential Privacy for Bandits
Achraf Azize, Debabrota Basu
Bandits serve as the theoretical foundation of sequential learning and an algorithmic foundation of modern recommender systems. However, recommender systems often rely on user-sens…
A Virtual-Force Based Swarm Algorithm for Balanced Circular Bin Packing Problems
Juliette Gamot, Mathieu Balesdent, Romain Wuilbercq +3
Balanced circular bin packing problems consist in positioning a given number of weighted circles in order to minimize the radius of a circular container while satisfying equilibriu…
Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning
Hector Kohler, Riad Akrour, Philippe Preux
Interpretability of AI models allows for user safety checks to build trust in these models. In particular, decision trees (DTs) provide a global view on the learned model and clear…
An Open Source Design Optimization Toolbox Evaluated on a Soft Finger
Stefan Escaida Navarro, Tanguy Navez, Olivier Goury +2
In this paper, we introduce a novel open source toolbox for design optimization in Soft Robotics. We consider that design optimization is an important trend in Soft Robotics that i…
Operational Research: Methods and Applications
Fotios Petropoulos, Gilbert Laporte, Emel Aktas +79
Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This…
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer
Hannes Eriksson, Debabrota Basu, Tommy Tram +2
In this paper, we study the problem of transferring the available Markov Decision Process (MDP) models to learn and plan efficiently in an unknown but similar MDP. We refer to it a…
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
We study differentially private (DP) machine learning algorithms as instances of noisy fixed-point iterations, in order to derive privacy and utility results from this well-studied…
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data
Pratik Karmakar, Debabrota Basu
We study design of black-box model extraction attacks that can send minimal number of queries from a publicly available dataset to a target ML model through a predictive API with a…
Anaphora Resolution in Dialogue: System Description (CODI-CRAC 2022 Shared Task)
Tatiana Anikina, Natalia Skachkova, Joseph Renner +1
We describe three models submitted for the CODI-CRAC 2022 shared task. To perform identity anaphora resolution, we test several combinations of the incremental clustering approach…