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04/30/2023
Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search
Graph neural networks are useful for learning problems, as well as for c...
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04/28/2023
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
We study K-armed bandit problems where the reward distributions of the a...
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10/30/2022
Revisiting Simple Regret Minimization in Multi-Armed Bandits
Simple regret is a natural and parameter-free performance criterion for ...
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10/25/2022
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits
In sparse linear bandits, a learning agent sequentially selects an actio...
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05/03/2022
Norm-Agnostic Linear Bandits
Linear bandits have a wide variety of applications including recommendat...
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02/04/2022
An Experimental Design Approach for Regret Minimization in Logistic Bandits
In this work we consider the problem of regret minimization for logistic...
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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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11/05/2021
Maillard Sampling: Boltzmann Exploration Done Optimally
The PhD thesis of Maillard (2013) presents a randomized algorithm for th...
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11/05/2021
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs
In online learning problems, exploiting low variance plays an important ...
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02/04/2021
Transfer Learning in Bandits with Latent Continuity
Structured stochastic multi-armed bandits provide accelerated regret rat...
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11/23/2020
Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits
We propose improved fixed-design confidence bounds for the linear logist...
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06/15/2020
Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
We study stochastic structured bandits for minimizing regret. The fact t...
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05/25/2019
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration
In this paper, we consider the nonparametric least square regression in ...
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02/05/2019
Parameter-free Online Convex Optimization with Sub-Exponential Noise
We consider the problem of unconstrained online convex optimization (OCO...
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01/08/2019
Bilinear Bandits with Low-rank Structure
We introduce the bilinear bandit problem with low-rank structure where a...
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10/29/2018
Adversarial Attacks on Stochastic Bandits
We study adversarial attacks that manipulate the reward signals to contr...
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08/17/2018
Data Poisoning Attacks in Contextual Bandits
We study offline data poisoning attacks in contextual bandits, a class o...
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11/06/2017
Online Learning for Changing Environments using Coin Betting
A key challenge in online learning is that classical algorithms can be s...
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06/01/2017
Scalable Generalized Linear Bandits: Online Computation and Hashing
Generalized Linear Bandits (GLBs), a natural extension of the stochastic...
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10/14/2016
Improved Strongly Adaptive Online Learning using Coin Betting
This paper describes a new parameter-free online learning algorithm for ...
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09/03/2016