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Tao

Seminar28042015

April 28th

14:30 , R2014 Digiteo Shannon (660) (see location):


Vianney Perchet



Title: Optimal Sample Size in Multi-Phase Learning


Abstract :


Motivated by practical applications, chiefly clinical trials, we study the regret achievable for stochastic multi-armed bandits under the constraint that the employed policy must function in a small number of phases. Our results show that a very small number of phases gives already close to minimax optimal regret bounds and we also evaluate the number of trials in each phase.


Contact: cyril.furtlehner à inria.fr

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Page dernièrement modifiée le Mardi 21 avril 2015 11:16:03 CEST par furtlehn.