What is recorded here?
Selected channels using sampled next-layer responses and a greedy reconstruction objective, then pruned corresponding filters and fine-tuned the narrowed network.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Retaining network structure means topology, not unchanged channel counts. Reconstruction selection is NP-hard and the implemented greedy solution is suboptimal; sampled reconstruction is not exact function preservation or a guarantee of classification accuracy. Training data, fine-tuning and deployment kernels remain part of the cost.
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People and systems
Jian-Hao Luo; Jianxin Wu; Weiyao Lin
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
ThiNet: next-layer reconstruction for structured channel pruning
Selected channels using sampled next-layer responses and a greedy reconstruction objective, then pruned corresponding filters and fine-tuned the narrowed network.
Scientific scope
Retaining network structure means topology, not unchanged channel counts. Reconstruction selection is NP-hard and the implemented greedy solution is suboptimal; sampled reconstruction is not exact function preservation or a guarantee of classification accuracy. Training data, fine-tuning and deployment kernels remain part of the cost.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Jian-Hao Luo; Jianxin Wu; Weiyao Lin
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.