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On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain
  Adaptation

On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation

1 February 2022
Maohao Shen
Yuheng Bu
Greg Wornell
ArXivPDFHTML

Papers citing "On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation"

5 / 5 papers shown
Title
Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation
Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation
Zhen Zhang
Bingsheng He
113
2
0
05 Feb 2025
A Comprehensive Survey on Source-free Domain Adaptation
A Comprehensive Survey on Source-free Domain Adaptation
Zhiqi Yu
Jingjing Li
Zhekai Du
Lei Zhu
Jikang Cheng
TTA
58
97
0
23 Feb 2023
Source-Free Unsupervised Domain Adaptation: A Survey
Source-Free Unsupervised Domain Adaptation: A Survey
Yuqi Fang
P. Yap
W. Lin
Hongtu Zhu
Mingxia Liu
157
91
0
31 Dec 2022
Domain Impression: A Source Data Free Domain Adaptation Method
Domain Impression: A Source Data Free Domain Adaptation Method
V. Kurmi
Venkatesh Subramanian
Vinay P. Namboodiri
TTA
151
150
0
17 Feb 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Yogesh S Rawat
M. Shah
259
510
0
15 Jan 2021
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