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Mitigating Sampling Bias and Improving Robustness in Active Learning

Mitigating Sampling Bias and Improving Robustness in Active Learning

13 September 2021
R. Krishnan
Alok Sinha
Nilesh A. Ahuja
Mahesh Subedar
Omesh Tickoo
R. Iyer
ArXiv (abs)PDFHTML

Papers citing "Mitigating Sampling Bias and Improving Robustness in Active Learning"

6 / 6 papers shown
Title
Dependency-aware Maximum Likelihood Estimation for Active Learning
Beyza Kalkanli
Tales Imbiriba
Stratis Ioannidis
Deniz Erdogmus
Jennifer Dy
61
0
0
07 Mar 2025
DEUCE: Dual-diversity Enhancement and Uncertainty-awareness for Cold-start Active Learning
DEUCE: Dual-diversity Enhancement and Uncertainty-awareness for Cold-start Active Learning
Jiaxin Guo
Cheng Chen
Shuzhen Li
Tianze Zhang
142
0
0
01 Feb 2025
Overcoming Overconfidence for Active Learning
Overcoming Overconfidence for Active Learning
Yujin Hwang
Won Jo
Juyoung Hong
Yukyung Choi
59
1
0
21 Aug 2023
D-CALM: A Dynamic Clustering-based Active Learning Approach for
  Mitigating Bias
D-CALM: A Dynamic Clustering-based Active Learning Approach for Mitigating Bias
Sabit Hassan
Malihe Alikhani
AI4CE
63
10
0
26 May 2023
Active Learning with Combinatorial Coverage
Active Learning with Combinatorial Coverage
Sai Prathyush Katragadda
Tyler Cody
Peter A. Beling
Laura J. Freeman
53
6
0
28 Feb 2023
Multi-Domain Active Learning: Literature Review and Comparative Study
Multi-Domain Active Learning: Literature Review and Comparative Study
Ruidan He
Shengcai Liu
Shan He
Ke Tang
OOD
85
14
0
25 Jun 2021
1