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07/01/2023
Adaptive Algorithms for Relaxed Pareto Set Identification
In this paper we revisit the fixed-confidence identification of the Pare...
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06/23/2023
Active Coverage for PAC Reinforcement Learning
Collecting and leveraging data with good coverage properties plays a cru...
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05/25/2023
An Īµ-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond
We propose EB-TCĪµ, a novel sampling rule for Īµ-best arm identification i...
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10/03/2022
Dealing with Unknown Variances in Best-Arm Identification
The problem of identifying the best arm among a collection of items havi...
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07/12/2022
Optimistic PAC Reinforcement Learning: the Instance-Dependent View
Optimistic algorithms have been extensively studied for regret minimizat...
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06/13/2022
Top Two Algorithms Revisited
Top Two algorithms arose as an adaptation of Thompson sampling to best a...
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05/31/2022
Near-Optimal Collaborative Learning in Bandits
This paper introduces a general multi-agent bandit model in which each a...
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03/21/2022
Efficient Algorithms for Extreme Bandits
In this paper, we contribute to the Extreme Bandit problem, a variant of...
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03/17/2022
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
In probably approximately correct (PAC) reinforcement learning (RL), an ...
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03/18/2021
Top-m identification for linear bandits
Motivated by an application to drug repurposing, we propose the first al...
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12/10/2020
Thompson Sampling for CVaR Bandits
Risk awareness is an important feature to formulate a variety of real wo...
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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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10/07/2020
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited
In this paper, we propose new problem-independent lower bounds on the sa...
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07/27/2020
Fast active learning for pure exploration in reinforcement learning
Realistic environments often provide agents with very limited feedback. ...
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07/09/2020
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
In this work, we propose KeRNS: an algorithm for episodic reinforcement ...
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06/11/2020
Adaptive Reward-Free Exploration
Reward-free exploration is a reinforcement learning setting recently stu...
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06/10/2020
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
We propose MDP-GapE, a new trajectory-based Monte-Carlo Tree Search algo...
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04/12/2020
Regret Bounds for Kernel-Based Reinforcement Learning
We consider the exploration-exploitation dilemma in finite-horizon reinf...
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12/06/2019
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling
Stochastic Rank-One Bandits (Katarya et al, (2017a,b)) are a simple fram...
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10/24/2019
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification
We investigate and provide new insights on the sampling rule called Top-...
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05/09/2019
Non-Asymptotic Sequential Tests for Overlapping Hypotheses and application to near optimal arm identification in bandit models
In this paper, we study sequential testing problems with overlapping hyp...
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03/17/2019
On Multi-Armed Bandit Designs for Phase I Clinical Trials
We study the problem of finding the optimal dosage in a phase I clinical...
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02/05/2019
The Generalized Likelihood Ratio Test meets klUCB: an Improved Algorithm for Piece-Wise Non-Stationary Bandits
We propose a new algorithm for the piece-wise non-stationary bandit pro...
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02/04/2019
New Algorithms for Multiplayer Bandits when Arm Means Vary Among Players
We study multiplayer stochastic multi-armed bandit problems in which the...
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11/28/2018
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals
This paper presents new deviation inequalities that are valid uniformly ...
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07/02/2018
Multi-Armed Bandit Learning in IoT Networks: Learning helps even in non-stationary settings
Setting up the future Internet of Things (IoT) networks will require to ...
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06/04/2018
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling
Learning the minimum/maximum mean among a finite set of distributions is...
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03/19/2018
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits
An online reinforcement learning algorithm is anytime if it does not nee...
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03/13/2018
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence
We consider the problem of near-optimal arm identification in the fixed ...
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11/07/2017
Multi-Player Bandits Models Revisited
Multi-player Multi-Armed Bandits (MAB) have been extensively studied in ...
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08/16/2017
Corrupt Bandits for Preserving Local Privacy
We study a variant of the stochastic multi-armed bandit (MAB) problem in...
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06/09/2017
Monte-Carlo Tree Search by Best Arm Identification
Recent advances in bandit tools and techniques for sequential learning a...
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01/31/2017
Learning the distribution with largest mean: two bandit frameworks
Over the past few years, the multi-armed bandit model has become increas...
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06/30/2016
Asymptotically Optimal Algorithms for Budgeted Multiple Play Bandits
We study a generalization of the multi-armed bandit problem with multipl...
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02/15/2016
Maximin Action Identification: A New Bandit Framework for Games
We study an original problem of pure exploration in a strategic bandit m...
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02/15/2016
Optimal Best Arm Identification with Fixed Confidence
We give a complete characterization of the complexity of best-arm identi...
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01/06/2016
On Bayesian index policies for sequential resource allocation
This paper is about index policies for minimizing (frequentist) regret i...
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06/12/2015
A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks
This paper presents a novel spectral algorithm with additive clustering ...
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07/16/2014
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
The stochastic multi-armed bandit model is a simple abstraction that has...
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05/13/2014
On the Complexity of A/B Testing
A/B testing refers to the task of determining the best option among two ...
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07/12/2013
Thompson Sampling for 1-Dimensional Exponential Family Bandits
Thompson Sampling has been demonstrated in many complex bandit models, h...
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05/18/2012
