Yinglun Zhu | DeepAI

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Featured Co-authors

Quanquan Gu
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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...

0 Jifan Zhang, et al. ∙

∙ 02/16/2023

Infinite Action Contextual Bandits with Reusable Data Exhaust

For infinite action contextual bandits, smoothed regret and reduction to...

0 Mark Rucker, et al. ∙

∙ 10/15/2022

Active Learning with Neural Networks: Insights from Nonparametric Statistics

Deep neural networks have great representation power, but typically requ...

0 Yinglun Zhu, et al. ∙

∙ 07/12/2022

Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces

Designing efficient general-purpose contextual bandit algorithms that wo...

0 Yinglun Zhu, et al. ∙

∙ 07/12/2022

Contextual Bandits with Large Action Spaces: Made Practical

A central problem in sequential decision making is to develop algorithms...

0 Yinglun Zhu, et al. ∙

∙ 03/31/2022

Efficient Active Learning with Abstention

The goal of active learning is to achieve the same accuracy achievable b...

0 Yinglun Zhu, et al. ∙

∙ 09/10/2021

Near Instance Optimal Model Selection for Pure Exploration Linear Bandits

The model selection problem in the pure exploration linear bandit settin...

0 Yinglun Zhu, et al. ∙

∙ 06/22/2021

Pure Exploration in Kernel and Neural Bandits

We study pure exploration in bandits, where the dimension of the feature...

20 Yinglun Zhu, et al. ∙

∙ 02/12/2021

Pareto Optimal Model Selection in Linear Bandits

We study a model selection problem in the linear bandit setting, where t...

0 Yinglun Zhu, et al. ∙

∙ 09/21/2020

Robust Outlier Arm Identification

We study the problem of Robust Outlier Arm Identification (ROAI), where ...

0 Yinglun Zhu, et al. ∙

∙ 06/26/2020

On Regret with Multiple Best Arms

We study regret minimization problem with the existence of multiple best...

0 Yinglun Zhu, et al. ∙

∙ 12/21/2017

ReabsNet: Detecting and Revising Adversarial Examples

Though deep neural network has hit a huge success in recent studies and ...

0 Jiefeng Chen, et al. ∙

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