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MPS: Metric-aware Pseudo-label Selection Framework via Reinforcement Learning
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Title
MPS: Metric-aware Pseudo-label Selection Framework via Reinforcement Learning
DGIST Authors
Seong Gyeom KimJin Ho ChangSung Hoon Im
Advisor
장진호
Co-Advisor(s)
Sung Hoon Im
Issued Date
2025
Awarded Date
2025-02-01
Citation
Seong Gyeom Kim. (2025). MPS: Metric-aware Pseudo-label Selection Framework via Reinforcement Learning. doi: 10.22677/THESIS.200000839746
Type
Thesis
Description
Machine Learning
Table Of Contents
Ⅰ. Introduction
1 Introduction 1
ⅠI. Related work
2.1 Pseudo-label 3
2.2 Reinforcement learning 4
ⅠII. Method
3.1 Pre-trained teacher model optimize and pseudo labeling 8
3.2 Training data sampling by contribution 9
3.2.1 Task predictor optimization 9
3.2.2 Controller optimization 10
3.3 The reinforcement learning algorithm 10
3.4 Data contribution evaluation using reinforcement learning 14
IV. Experiments
4.1 Implement details 15
4.2 Result 17
4.2.1 SSL with selected data 17
4.2.2 Analysis 19
4.2.3 Discussion 20
V. Conclusion
5 Conclusion 22
URI
http://hdl.handle.net/20.500.11750/58098
http://dgist.dcollection.net/common/orgView/200000839746
DOI
10.22677/THESIS.200000839746
Degree
Master
Department
Artificial Intelligence Major
Publisher
DGIST
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