Zobrazeno 1 - 10
of 808
pro vyhledávání: '"Gouverneur P"'
Autor:
Bongole, Raghav, Gouverneur, Amaury, Rodríguez-Gálvez, Borja, Oechtering, Tobias J., Skoglund, Mikael
We study agents acting in an unknown environment where the agent's goal is to find a robust policy. We consider robust policies as policies that achieve high cumulative rewards for all possible environments. To this end, we consider agents minimizing
Externí odkaz:
http://arxiv.org/abs/2410.16013
This paper studies the Bayesian regret of a variant of the Thompson-Sampling algorithm for bandit problems. It builds upon the information-theoretic framework of [Russo and Van Roy, 2015] and, more specifically, on the rate-distortion analysis from [
Externí odkaz:
http://arxiv.org/abs/2403.03361
Autor:
Pourjavan S, Gouverneur F, Macq B, Van Drooghenbroeck T, De Potter P, Boschi A, El Maftouhi A
Publikováno v:
Clinical Ophthalmology, Vol Volume 18, Pp 3493-3502 (2024)
Sayeh Pourjavan,1 François Gouverneur,2 Benoit Macq,2 Thomas Van Drooghenbroeck,2 Patrick De Potter,1 Antonella Boschi,1 Adil El Maftouhi3 1Department of Ophthalmology, Cliniques Universitaires Saint Luc, UCL, Brussels, Belgium; 2Institute for Infor
Externí odkaz:
https://doaj.org/article/7580db792ca44369bc256759eb979550
Autor:
Philip Gouverneur, Aleksandra Badura, Frédéric Li, Maria Bieńkowska, Luisa Luebke, Wacław M. Adamczyk, Tibor M. Szikszay, Andrzej Myśliwiec, Kerstin Luedtke, Marcin Grzegorzek, Ewa Piętka
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract Access to large amounts of data is essential for successful machine learning research. However, there is insufficient data for many applications, as data collection is often challenging and time-consuming. The same applies to automated pain
Externí odkaz:
https://doaj.org/article/732c751399f841b68cd8e60ceb963fce
In this work, we study the performance of the Thompson Sampling algorithm for Contextual Bandit problems based on the framework introduced by Neu et al. and their concept of lifted information ratio. First, we prove a comprehensive bound on the Thomp
Externí odkaz:
http://arxiv.org/abs/2304.13593
Autor:
Thomas Joris, Thomas Jouant, Jean-Rock Jacques, Lorian Gouverneur, Xavier Saintmard, Lea Vilanova Mañá, Majeed Jamakhani, Michal Reichert, Luc Willems
Publikováno v:
PLoS Pathogens, Vol 20, Iss 11, p e1012659 (2024)
In sheep infected with bovine leukemia virus (BLV), transcription of structural, enzymatic, and accessory genes is silenced. However, the BLV provirus transcribes a series of non-coding RNAs that remain undetected by the host immune response. Specifi
Externí odkaz:
https://doaj.org/article/8b025b9594e8476e8819aaf694feaf84
Autor:
Pascal Demoly, Mathieu Molimard, Jean-François Bergmann, Bertrand Delaisi, Amandine Gouverneur, Jade Vadel, Cédric Collin, Laurence Girard, Silvia Scurati, Philippe Devillier
Publikováno v:
The Lancet Regional Health. Europe, Vol 46, Iss , Pp 101120- (2024)
Externí odkaz:
https://doaj.org/article/ce9e63e521824bfa8837e1fa305a6523
Building on the framework introduced by Xu and Raginksy [1] for supervised learning problems, we study the best achievable performance for model-based Bayesian reinforcement learning problems. With this purpose, we define minimum Bayesian regret (MBR
Externí odkaz:
http://arxiv.org/abs/2207.08735
Autor:
Pascal Demoly, Mathieu Molimard, Jean-François Bergmann, Bertrand Delaisi, Amandine Gouverneur, Jade Vadel, Cédric Collin, Laurence Girard, Silvia Scurati, Philippe Devillier
Publikováno v:
The Lancet Regional Health. Europe, Vol 41, Iss , Pp 100915- (2024)
Summary: Background: The only disease-modifying treatment currently available for allergic rhinitis (AR) is allergen immunotherapy (AIT). The main objective of the EfficAPSI real-world study (RWS) was to evaluate the impact of liquid sublingual immun
Externí odkaz:
https://doaj.org/article/1cf18a041ca64146a66feda95bb63ba1
The problem of the optimal allocation (in the expected mean square error sense) of a measurement budget for particle filtering is addressed. We propose three different optimal intermittent filters, whose optimality criteria depend on the information
Externí odkaz:
http://arxiv.org/abs/2204.06265