Channel-Prioritized Convolutional Neural Networks for Sparsity and Multi-fidelity
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Updated
Feb 23, 2018 - Python
Channel-Prioritized Convolutional Neural Networks for Sparsity and Multi-fidelity
Deep Face Model Compression
Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.
Extremely light-weight MixNet with Top-1 75.7% and 2.5M params
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen, and Chu-Song Chen, "Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications," IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2018
Exploring Variational Deep Q Networks. A study undertaken for the University of Cambridge's R244 Computer Science Masters Course. Inspired by https://arxiv.org/abs/1711.11225/.
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
Cheng-En Wu, Yi-Ming Chan and Chu-Song Chen "On Merging MobileNets for Efficient Multitask Inference", International Symposium on High-Performance Computer Architecture(HPCA) on Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications(EMC2), 2019
[ECCV 2020] Code release for "Resolution Switchable Networks for Runtime Efficient Image Recognition"
[MicroNet Challenge (NeurIPS 2019 )] "Adjustable Quantization: Jointly Learn the Bit-width and Weight in DNN Training" by Yonggan Fu, Ruiyang Zhao, Yue Wang, Chaojian Li, Haoran You, Zhangyang Wang, Yingyan Lin
Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan and Chu-Song Chen, "Pruning Depthwise Separable Convolutions for MobileNet Compression," International Joint Conference on Neural Networks, IJCNN 2020, July 2020.
Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu-Song Chen, "Unifying and Merging Well-trained Deep Neural Networks for Inference Stage," International Joint Conference on Artificial Intelligence (IJCAI), 2018
Implementation of AAAI 21 paper: Nested Named Entity Recognition with Partially Observed TreeCRFs
Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'
Code for IoT paper 'Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices'
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
[CVPR 2021] Exploring Sparsity in Image Super-Resolution for Efficient Inference
A Post-Training Quantizer for the Design of Mixed Low-Precision DNNs with Dynamic Fixed-Point Representation for Efficient Hardware Acceleration on Edge Devices
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