Early Pruning
Early Pruning is a model optimization technique in machine learning wherein redundant or less significant parameters are removed during the initial stages of training, distinguishing it from later pruning strategies by its timing and its emphasis on reducing computational burden from the outset.
48
Publications
2.4K
Citations
173
Authors
97
Institutions
Publications per year
2017–2026
14
Parents
48
Large-scale malware indexing using function-call graphs
Xin Hu, Tzi‐cker Chiueh, Kang G. Shin · 2009 · 316 citations
Haemodynamics-Driven Developmental Pruning of Brain Vasculature in Zebrafish
Qi Chen, Luan Jiang, Chun Li et al. · PLoS Biology · 2012 · 267 citations · Full text
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Ho Chi Minh City University of Technology
Ho Chi Minh City, Vietnam
2 h-index
2 publications
47 citations

Vietnam National University Ho Chi Minh City
Ho Chi Minh City, Vietnam
2 h-index
3 publications
67 citations

City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
3 publications
135 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
5 publications
249 citations

Sejong University
Seoul, South Korea
2 h-index
2 publications
81 citations
The Ohio State University
Columbus, United States
2 h-index
4 publications
152 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
11 publications
1.5K citations
HUTECH University
Ho Chi Minh City, Vietnam
2 h-index
2 publications
47 citations
1–8 of 97
Repository · 2 publications · 105 citations
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1 publications · 61 citations
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1 publications · 35 citations
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1 publications · 267 citations
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1 publications · 27 citations
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