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09/06/2023
Near-continuous time Reinforcement Learning for continuous state-action spaces
We consider the Reinforcement Learning problem of controlling an unknown...
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01/06/2022
Jointly Efficient and Optimal Algorithms for Logistic Bandits
Logistic Bandits have recently undergone careful scrutiny by virtue of t...
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03/09/2021
Regret Bounds for Generalized Linear Bandits under Parameter Drift
Generalized Linear Bandits (GLBs) are powerful extensions to the Linear ...
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10/23/2020
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Logistic Bandits have recently attracted substantial attention, by provi...
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10/20/2020
Real-Time Optimisation for Online Learning in Auctions
In display advertising, a small group of sellers and bidders face each o...
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07/13/2020
Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
We study the exploration-exploitation dilemma in the linear quadratic re...
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02/18/2020
Improved Optimistic Algorithms for Logistic Bandits
The generalized linear bandit framework has attracted a lot of attention...
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10/12/2019
Thompson Sampling in Non-Episodic Restless Bandits
Restless bandit problems assume time-varying reward distributions of the...
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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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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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03/27/2017
Thompson Sampling for Linear-Quadratic Control Problems
We consider the exploration-exploitation tradeoff in linear quadratic (L...
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11/20/2016