Dimitrakakis, Christos

Nom

Dimitrakakis, Christos

Affiliation principale

Institut d'informatique

Fonction

Professor

Email

christos.dimitrakakis@unine.ch

Identifiants

https://libra.unine.ch/handle/123456789/30936

_

0000-0002-5367-5189

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Accès libre
On The Differential Privacy of Thompson Sampling With Gaussian Prior
(2018-06-24T18:37:09Z)
Aristide C. Y. Tossou
;
Dimitrakakis, Christos
We show that Thompson Sampling with Gaussian Prior as detailed by Algorithm 2 in (Agrawal & Goyal, 2013) is already differentially private. Theorem 1 show that it enjoys a very competitive privacy loss of only O(ln2T) after T rounds. Finally, Theorem 2 show that one can control the privacy loss to any desirable ϵ level by appropriately increasing the variance of the samples from the Gaussian posterior. And this increases the regret only by a term of O(ln2Tϵ). This compares favorably to the previous result for Thompson Sampling in the literature ((Mishra & Thakurta, 2015)) which adds a term of O(Kln3Tϵ2) to the regret in order to achieve the same privacy level. Furthermore, our result use the basic Thompson Sampling with few modifications whereas the result of (Mishra & Thakurta, 2015) required sophisticated constructions.