Global Channel Pruning With Self-Supervised Mask Learning
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3488098
Abstract: Network pruning is widely used in model compression due to its simplicity and efficiency. Existing methods typically introduce sparse loss regularization to learn masks. However, this sparse regularization approach lacks a clear criterion for evaluating… read more here.
Keywords: supervised mask; self supervised; channel pruning; global channel ... See more keywords
Performance-aware Approximation of Global Channel Pruning for Multitask CNNs
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.48550/arxiv.2303.11923
Abstract: Global channel pruning (GCP) aims to remove a subset of channels (filters) across different layers from a deep model without hurting the performance. Previous works focus on either single task model pruning or simply adapting… read more here.
Keywords: performance aware; global channel; task; channel pruning ... See more keywords