Theoretical Computer Science Spring School: Machine Learning / Ecole de Printemps d'Informatique Théorique : Apprentissage Automatique

Collection Theoretical Computer Science Spring School: Machine Learning / Ecole de Printemps d'Informatique Théorique : Apprentissage Automatique

Organizer(s) Cappé, Olivier ; Garivier, Aurélien ; Gribonval, Rémi ; Kaufmann, Emilie ; Vernade, Claire

Date(s) 23/05/2022 - 27/05/2022

linked URL https://conferences.cirm-math.fr/2542.html

00:00:00 / 00:00:00

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Multi-armed bandits and beyond

By Shipra Agrawal

In this tutorial I will discuss recent advances in theory of multi-armed bandits and reinforcement learning, in particular the upper confidence bound (UCB) and Thompson Sampling (TS) techniques for algorithm design and analysis.

Information about the video

Date of recording 23/05/2022
Date of publication 21/06/2022
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers, Graduate Students
Director(s) Jean Petit
Format MP4

Citation data

DOI 10.24350/CIRM.V.19921203
Cite this video Agrawal, Shipra (23/05/2022). Multi-armed bandits and beyond. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19921203
URL https://dx.doi.org/10.24350/CIRM.V.19921203

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