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02/07/2022
Training OOD Detectors in their Natural Habitats
Out-of-distribution (OOD) detection is important for machine learning mo...
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02/03/2022
GALAXY: Graph-based Active Learning at the Extreme
Active learning is a label-efficient approach to train highly effective ...
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11/09/2021
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers
We consider interactive learning in the realizable setting and develop a...
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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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05/13/2021
Improved Algorithms for Agnostic Pool-based Active Classification
We consider active learning for binary classification in the agnostic po...
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05/12/2021
High-Dimensional Experimental Design and Kernel Bandits
In recent years methods from optimal linear experimental design have bee...
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11/01/2020
Experimental Design for Regret Minimization in Linear Bandits
In this paper we propose a novel experimental design-based algorithm to ...
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06/21/2020
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
This paper proposes near-optimal algorithms for the pure-exploration lin...
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06/15/2019
The True Sample Complexity of Identifying Good Arms
We consider two multi-armed bandit problems with n arms: (i) given an ϵ ...
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09/30/2017
Decontamination of Mutual Contamination Models
Many machine learning problems can be characterized by mutual contaminat...
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05/24/2017
Nonparametric Preference Completion
We consider the task of collaborative preference completion: given a poo...
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02/19/2016
