Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition
Authors: Marawan Gamal Abdel Hameed, Marzieh S. Tahaei, Ali Mosleh, Vahid Partovi Nia771-779
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results for image classification on CIFAR-10 and Image Net datasets using Res Net, Mobile Netv2 and Se Net architectures substantiate the effectiveness of our proposed approach. We find that GKPD outperforms state-of-the-art decomposition methods including Tensor-Train and Tensor-Ring as well as other relevant compression methods such as pruning and knowledge distillation. |
| Researcher Affiliation | Collaboration | Marawan Gamal Abdel Hameed 1,2*, Marzieh S. Tahaei1 , Ali Mosleh1, Vahid Partovi Nia1 1Noah s Ark Lab, Huawei Technologies Canada 2University of Waterloo |
| Pseudocode | Yes | Algorithm 1: Forward Pass |
| Open Source Code | No | The paper does not provide an explicit statement or link for open-source code for the described methodology. |
| Open Datasets | Yes | Experimental results for image classification on CIFAR-10 and Image Net datasets... Table 1 shows the top-1 accuracy on the CIFAR-10 (Krizhevsky 2009) dataset... on a larger scale dataset i.e, Image Net (Krizhevsky, Sutskever, and Hinton 2012). |
| Dataset Splits | Yes | Experimental results for image classification on CIFAR-10 and Image Net datasets... Top-1 accuracy measured on CIFAR-10... Top-1 accuracy measured on Image Net. These are well-established benchmark datasets with standard train/validation/test splits, which are implicitly used for evaluating performance. |
| Hardware Specification | No | The paper does not explicitly describe the specific hardware (e.g., GPU models, CPU types) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | No | The paper states 'We provide implementation details in the Supplementary Material' but does not include specific hyperparameters or training settings in the main text. |