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06/16/2023
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning
Labeled data are critical to modern machine learning applications, but o...
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02/16/2023
Infinite Action Contextual Bandits with Reusable Data Exhaust
For infinite action contextual bandits, smoothed regret and reduction to...
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10/15/2022
Active Learning with Neural Networks: Insights from Nonparametric Statistics
Deep neural networks have great representation power, but typically requ...
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07/12/2022
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces
Designing efficient general-purpose contextual bandit algorithms that wo...
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07/12/2022
Contextual Bandits with Large Action Spaces: Made Practical
A central problem in sequential decision making is to develop algorithms...
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03/31/2022
Efficient Active Learning with Abstention
The goal of active learning is to achieve the same accuracy achievable b...
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09/10/2021
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits
The model selection problem in the pure exploration linear bandit settin...
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06/22/2021
Pure Exploration in Kernel and Neural Bandits
We study pure exploration in bandits, where the dimension of the feature...
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02/12/2021
Pareto Optimal Model Selection in Linear Bandits
We study a model selection problem in the linear bandit setting, where t...
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09/21/2020
Robust Outlier Arm Identification
We study the problem of Robust Outlier Arm Identification (ROAI), where ...
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06/26/2020
On Regret with Multiple Best Arms
We study regret minimization problem with the existence of multiple best...
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12/21/2017
