Search Results for author: Shaowu Chen

Found 4 papers, 3 papers with code

P-ROCKET: Pruning Random Convolution Kernels for Time Series Classification

1 code implementation15 Sep 2023 Shaowu Chen, Weize Sun, Lei Huang, Xiaopeng Li, Qingyuan Wang, Deepu John

Stage 1 of P-ROCKET employs group-wise regularization similarly to our initial ADMM-based Algorithm, but introduces dynamically varying penalties to greatly accelerate the process.

Evolutionary Algorithms feature selection +2

WHC: Weighted Hybrid Criterion for Filter Pruning on Convolutional Neural Networks

1 code implementation16 Feb 2023 Shaowu Chen, Weize Sun, Lei Huang

Filter pruning has attracted increasing attention in recent years for its capacity in compressing and accelerating convolutional neural networks.

Classification Network Pruning +1

Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning

no code implementations22 Oct 2022 Xuhua Li, Weize Sun, Lei Huang, Shaowu Chen

Filter pruning is a common method to achieve model compression and acceleration in deep neural networks (DNNs). Some research regarded filter pruning as a combinatorial optimization problem and thus used evolutionary algorithms (EA) to prune filters of DNNs.

Combinatorial Optimization Evolutionary Algorithms +1

Joint Matrix Decomposition for Deep Convolutional Neural Networks Compression

1 code implementation9 Jul 2021 Shaowu Chen, Jiahao Zhou, Weize Sun, Lei Huang

To overcome this problem, we propose to compress CNNs and alleviate performance degradation via joint matrix decomposition, which is different from existing works that compressed layers separately.

Efficient Neural Network Matrix Factorization / Decomposition +1

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