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09/01/2023
Local and adaptive mirror descents in extensive-form games
We study how to learn ϵ-optimal strategies in zero-sum imperfect informa...
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06/23/2023
Trading-off price for data quality to achieve fair online allocation
We consider the problem of online allocation subject to a long-term fair...
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06/13/2023
Online Matching in Geometric Random Graphs
In online advertisement, ad campaigns are sequentially displayed to user...
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06/03/2023
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation
Many machine learning problems require performing dataset valuation, i.e...
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03/16/2023
Addressing bias in online selection with limited budget of comparisons
Consider a hiring process with candidates coming from different universi...
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12/23/2022
Adapting to game trees in zero-sum imperfect information games
Imperfect information games (IIG) are games in which each player only pa...
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11/29/2022
A survey on multi-player bandits
Due mostly to its application to cognitive radio networks, multiplayer b...
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10/23/2022
Stochastic Mirror Descent for Large-Scale Sparse Recovery
In this paper we discuss an application of Stochastic Approximation to s...
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05/26/2022
Active Labeling: Streaming Stochastic Gradients
The workhorse of machine learning is stochastic gradient descent. To acc...
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02/15/2022
An algorithmic solution to the Blotto game using multi-marginal couplings
We describe an efficient algorithm to compute solutions for the general ...
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12/11/2021
Privacy Amplification via Shuffling for Linear Contextual Bandits
Contextual bandit algorithms are widely used in domains where it is desi...
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11/02/2021
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge
We consider the problem of online linear regression in the stochastic se...
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10/18/2021
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
In the fixed budget thresholding bandit problem, an algorithm sequential...
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07/31/2021
Pure Exploration and Regret Minimization in Matching Bandits
Finding an optimal matching in a weighted graph is a standard combinator...
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07/02/2021
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm
Motivated by sequential budgeted allocation problems, we investigate onl...
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06/10/2021
Unsupervised Neural Hidden Markov Models with a Continuous latent state space
We introduce a new procedure to neuralize unsupervised Hidden Markov Mod...
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06/09/2021
Offline Inverse Reinforcement Learning
The objective of offline RL is to learn optimal policies when a fixed ex...
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06/08/2021
Decentralized Learning in Online Queuing Systems
Motivated by packet routing in computer networks, online queuing systems...
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05/25/2021
A Generalised Inverse Reinforcement Learning Framework
The gloabal objective of inverse Reinforcement Learning (IRL) is to esti...
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03/17/2021
Homomorphically Encrypted Linear Contextual Bandit
Contextual bandit is a general framework for online learning in sequenti...
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02/16/2021
Making the most of your day: online learning for optimal allocation of time
We study online learning for optimal allocation when the resource to be ...
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01/04/2021
Be Greedy in Multi-Armed Bandits
The Greedy algorithm is the simplest heuristic in sequential decision pr...
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12/28/2020
Lifelong Learning in Multi-Armed Bandits
Continuously learning and leveraging the knowledge accumulated from prio...
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11/18/2020
Learning in repeated auctions
Auction theory historically focused on the question of designing the bes...
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11/09/2020
Robustness of Community Detection to Random Geometric Perturbations
We consider the stochastic block model where connection between vertices...
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10/15/2020
Local Differentially Private Regret Minimization in Reinforcement Learning
Reinforcement learning algorithms are widely used in domains where it is...
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07/20/2020
Speed of Social Learning from Reviews in Non-Stationary Environments
Potential buyers of a product or service tend to first browse feedback f...
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06/11/2020
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
We investigate stochastic combinatorial multi-armed bandit with semi-ban...
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05/04/2020
Categorized Bandits
We introduce a new stochastic multi-armed bandit setting where arms are ...
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02/04/2020
Selfish Robustness and Equilibria in Multi-Player Bandits
Motivated by cognitive radios, stochastic multi-player multi-armed bandi...
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09/15/2019
Adversarial learning for revenue-maximizing auctions
We introduce a new numerical framework to learn optimal bidding strategi...
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07/10/2019
Markov Decision Process for MOOC users behavioral inference
Studies on massive open online courses (MOOCs) users discuss the existen...
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06/20/2019
Active Linear Regression
We consider the problem of active linear regression where a decision mak...
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05/29/2019
Robust Stackelberg buyers in repeated auctions
We consider the practical and classical setting where the seller is usin...
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05/28/2019
Repeated A/B Testing
We study a setting in which a learner faces a sequence of A/B tests and ...
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05/27/2019
Private Learning and Regularized Optimal Transport
Private data are valuable either by remaining private (for instance if t...
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02/27/2019
Learning to bid in revenue-maximizing auctions
We consider the problem of the optimization of bidding strategies in pri...
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02/12/2019
A Problem-Adaptive Algorithm for Resource Allocation
We consider a sequential stochastic resource allocation problem under th...
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02/11/2019
Exploiting Structure of Uncertainty for Efficient Combinatorial Semi-Bandits
We improve the efficiency of algorithms for stochastic combinatorial sem...
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11/12/2018
A differential game on Wasserstein space. Application to weak approachability with partial monitoring
Studying continuous time counterpart of some discrete time dynamics is n...
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10/11/2018
Regularized Contextual Bandits
We consider the stochastic contextual bandit problem with additional reg...
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10/09/2018
Bridging the gap between regret minimization and best arm identification, with application to A/B tests
State of the art online learning procedures focus either on selecting th...
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09/21/2018
SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits
We consider the stochastic multiplayer multi-armed bandit problem, where...
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08/21/2018
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems
Second price auctions with reserve price are widely used by the main Int...
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07/10/2018
Bandits with Side Observations: Bounded vs. Logarithmic Regret
We consider the classical stochastic multi-armed bandit but where, from ...
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07/09/2018
Dynamic Pricing with Finitely Many Unknown Valuations
Motivated by posted price auctions where buyers are grouped in an unknow...
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06/06/2018
Finding the Bandit in a Graph: Sequential Search-and-Stop
We consider the problem where an agent wants to find a hidden object tha...
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05/01/2018
Explicit shading strategies for repeated truthful auctions
With the increasing use of auctions in online advertising, there has bee...
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04/03/2017
A comparative study of counterfactual estimators
We provide a comparative study of several widely used off-policy estimat...
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02/22/2017
