Light Pruning
Light Pruning is a pruning strategy in machine learning that removes a relatively small proportion of model parameters or connections, typically preserving the majority of the original network structure while aiming to maintain model performance with minor reductions in complexity.
7
Publications
148
Citations
22
Authors
8
Institutions
Publications per year
2017–2026
1
Parents
7
1–5 of 7
22
1
h-index
1
h-index
1
h-index
Eberswalde University for Sustainable Development, Germany
1 publications · 17 citations
1
h-index
1
h-index
1–5 of 22
8
University of Wisconsin–Stevens Point
Stevens Point, United States
1 h-index
1 publications
17 citations
The Ohio State University
Columbus, United States
1 h-index
2 publications
52 citations

Sun Yat-sen University
Guangzhou, China
1 h-index
2 publications
62 citations
Servicio Regional de Investigación y Desarrollo Agroalimentario
Villaviciosa, Spain
1 h-index
1 publications
10 citations
Universitat de València
Valencia, Spain
1 h-index
3 publications
30 citations
Dalian Dermatosis Hospital
Dalian, China
1 h-index
5 publications
155 citations
Centro Tecnológico de Automoción de Galicia
Porriño, Spain
1 h-index
1 publications
17 citations
Key Laboratory of Guangdong Province
Guangzhou, China
1 h-index
1 publications
31 citations
1–8 of 8
1 publications · 17 citations
1
h-index
1 publications · 31 citations
1
h-index
1 publications · 26 citations
1
h-index
1 publications · 10 citations
1
h-index
1 publications · 24 citations
1
h-index
1–5