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09/19/2023
Monte-Carlo tree search with uncertainty propagation via optimal transport
This paper introduces a novel backup strategy for Monte-Carlo Tree Searc...
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06/19/2023
AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents
The reproducibility of many experimental results in Deep Reinforcement L...
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10/05/2022
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning
We study the problem of episodic reinforcement learning in continuous st...
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09/15/2022
Risk-aware linear bandits with convex loss
In decision-making problems such as the multi-armed bandit, an agent lea...
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08/24/2022
Collaborative Algorithms for Online Personalized Mean Estimation
We consider an online estimation problem involving a set of agents. Each...
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03/07/2022
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm
In this paper, we study the stochastic bandits problem with k unknown he...
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01/18/2022
Bregman Deviations of Generic Exponential Families
We revisit the method of mixture technique, also known as the Laplace me...
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12/02/2021
Indexed Minimum Empirical Divergence for Unimodal Bandits
We consider a multi-armed bandit problem specified by a set of one-dimen...
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11/18/2021
From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic Bandits
The stochastic multi-arm bandit problem has been extensively studied und...
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10/27/2020
Sub-sampling for Efficient Non-Parametric Bandit Exploration
In this paper we propose the first multi-armed bandit algorithm based on...
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10/09/2020
Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients
Policy gradient algorithms have proven to be successful in diverse decis...
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09/09/2020
Improved Exploration in Factored Average-Reward MDPs
We consider a regret minimization task under the average-reward criterio...
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07/07/2020
Optimal Strategies for Graph-Structured Bandits
We study a structured variant of the multi-armed bandit problem specifie...
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06/30/2020
Forced-exploration free Strategies for Unimodal Bandits
We consider a multi-armed bandit problem specified by a set of Gaussian ...
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04/20/2020
Tightening Exploration in Upper Confidence Reinforcement Learning
The upper confidence reinforcement learning (UCRL2) strategy introduced ...
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02/25/2020
Robust Estimation, Prediction and Control with Linear Dynamics and Generic Costs
We develop a framework for the adaptive model predictive control of a li...
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10/09/2019
Model-Based Reinforcement Learning Exploiting State-Action Equivalence
Leveraging an equivalence property in the state-space of a Markov Decisi...
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05/30/2019
Distribution-dependent and Time-uniform Bounds for Piecewise i.i.d Bandits
We consider the setup of stochastic multi-armed bandits in the case when...
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05/27/2019
Learning Multiple Markov Chains via Adaptive Allocation
We study the problem of learning the transition matrices of a set of Mar...
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04/09/2019
Practical Open-Loop Optimistic Planning
We consider the problem of online planning in a Markov Decision Process ...
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03/01/2019
Approximate Robust Control of Uncertain Dynamical Systems
This work studies the design of safe control policies for large-scale no...
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03/05/2018
Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs
The problem of reinforcement learning in an unknown and discrete Markov ...
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08/31/2017
Efficient tracking of a growing number of experts
We consider a variation on the problem of prediction with expert advice,...
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08/02/2017
Streaming kernel regression with provably adaptive mean, variance, and regularization
We consider the problem of streaming kernel regression, when the observa...
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05/24/2017
Boundary Crossing Probabilities for General Exponential Families
We consider parametric exponential families of dimension K on the real l...
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09/07/2016