4 citations · 8 across the 7 of their papers we have counts for
7 papers
Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
Clémence Réda, Tomas Rigaux, Hiba Bederina +3
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also mi…
Embedding Learning on Multiplex Networks for Link Prediction
Orell Trautmann, Olaf Wolkenhauer, Clémence Réda
Over the past years, embedding learning on networks has shown tremendous results in link prediction tasks for complex systems, with a wide range of real-life applications. Learning…
Handling Missing Data in Downstream Tasks With Distribution-Preserving Guarantees
Rahul Bordoloi, Clémence Réda, Saptarshi Bej +1
Missing feature values are a significant hurdle for downstream machine-learning tasks such as classification. However, imputation methods for classification might be time-consuming…
An Anytime Algorithm for Good Arm Identification
Marc Jourdan, Andrée Delahaye-Duriez, Clémence Réda
In good arm identification (GAI), the goal is to identify one arm whose average performance exceeds a given threshold, referred to as a good arm, if it exists. Few works have studi…
Near-Optimal Collaborative Learning in Bandits
Clémence Réda, Sattar Vakili, Emilie Kaufmann
This paper introduces a general multi-agent bandit model in which each agent is facing a finite set of arms and may communicate with other agents through a central controller in or…
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
Clémence Réda, Andrea Tirinzoni, Rémy Degenne
We study the problem of the identification of m arms with largest means under a fixed error rate (fixed-confidence Top-m identification), for misspecified linear bandit models.…
Top-m identification for linear bandits
Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez
Motivated by an application to drug repurposing, we propose the first algorithms to tackle the identification of the m 1 arms with largest means in a linear bandit model, in…