17 citations · 36 across the 8 of their papers we have counts for
11 papers
Near-optimal Bayesian Solution For Unknown Discrete Markov Decision Process
Aristide Tossou, Christos Dimitrakakis, Debabrota Basu
We tackle the problem of acting in an unknown finite and discrete Markov Decision Process (MDP) for which the expected shortest path from any state to any other state is bounded by…
Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games
Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki +1
We study two-player general sum repeated finite games where the rewards of each player are generated from an unknown distribution. Our aim is to find the egalitarian bargaining sol…
Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities
Aristide Tossou, Debabrota Basu, Christos Dimitrakakis
We study model-based reinforcement learning in an unknown finite communicating Markov decision process. We propose a simple algorithm that leverages a variance based confidence int…
Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost?
Debabrota Basu, Christos Dimitrakakis, Aristide Tossou
Based on differential privacy (DP) framework, we introduce and unify privacy definitions for the multi-armed bandit algorithms. We represent the framework with a unified graphical…
On The Differential Privacy of Thompson Sampling With Gaussian Prior
Aristide C. Y. Tossou, Christos Dimitrakakis
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 com…
Learning to Match
Philip Ekman, Sebastian Bellevik, Christos Dimitrakakis +1
Outsourcing tasks to previously unknown parties is becoming more common. One specific such problem involves matching a set of workers to a set of tasks. Even if the latter have pre…
Thompson Sampling For Stochastic Bandits with Graph Feedback
Aristide C. Y. Tossou, Christos Dimitrakakis, Devdatt Dubhashi
We present a novel extension of Thompson Sampling for stochastic sequential decision problems with graph feedback, even when the graph structure itself is unknown and/or changing.…
Achieving Privacy in the Adversarial Multi-Armed Bandit
Aristide C. Y. Tossou, Christos Dimitrakakis
In this paper, we improve the previously best known regret bound to achieve -differential privacy in oblivious adversarial bandits from to $\mathcal{O…
Algorithms for Differentially Private Multi-Armed Bandits
Aristide Tossou, Christos Dimitrakakis
We present differentially private algorithms for the stochastic Multi-Armed Bandit (MAB) problem. This is a problem for applications such as adaptive clinical trials, experiment de…
Probabilistic inverse reinforcement learning in unknown environments
Aristide Tossou, Christos Dimitrakakis
We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to con…
Probabilistic inverse reinforcement learning in unknown environments
Aristide C. Y. Tossou, Christos Dimitrakakis
We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to con…