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On the Marginal Benefit of Active Learning: Does Self-Supervision Eat
  Its Cake?

On the Marginal Benefit of Active Learning: Does Self-Supervision Eat Its Cake?

16 November 2020
Yao-Chun Chan
Mingchen Li
Samet Oymak
    SSL
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Papers citing "On the Marginal Benefit of Active Learning: Does Self-Supervision Eat Its Cake?"

4 / 4 papers shown
Title
LabelBench: A Comprehensive Framework for Benchmarking Adaptive
  Label-Efficient Learning
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning
Jifan Zhang
Yifang Chen
Gregory H. Canal
Stephen Mussmann
Arnav M. Das
...
Yinglun Zhu
Jeffrey Bilmes
S. Du
Kevin G. Jamieson
Robert D. Nowak
VLM
38
10
0
16 Jun 2023
An Empirical Study on the Efficacy of Deep Active Learning for Image
  Classification
An Empirical Study on the Efficacy of Deep Active Learning for Image Classification
Yu Li
Mu-Hwa Chen
Yannan Liu
Daojing He
Qiang Xu
42
9
0
30 Nov 2022
A Comparative Survey of Deep Active Learning
A Comparative Survey of Deep Active Learning
Xueying Zhan
Qingzhong Wang
Kuan-Hao Huang
Haoyi Xiong
Dejing Dou
Antoni B. Chan
FedML
HAI
24
105
0
25 Mar 2022
Active Learning at the ImageNet Scale
Active Learning at the ImageNet Scale
Z. Emam
Hong-Min Chu
Ping Yeh-Chiang
W. Czaja
R. Leapman
Micah Goldblum
Tom Goldstein
32
34
0
25 Nov 2021
1