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Explanation Guided Knowledge Distillation for Pre-trained Language Model Compression 期刊论文
ACM Transactions on Asian and Low-Resource Language Information Processing, 2024, 卷号: 23, 期号: 2, 页码: 1-19
作者:  Zhao Yang;  Yuanzhe Zhang;  Dianbo Sui;  Yiming Ju;  Jun Zhao;  Kang Liu
Adobe PDF(1250Kb)  |  收藏  |  浏览/下载：32/13  |  提交时间：2024/05/30
Towards Automatic Model Compression via A Unified Two-Stage Framework 期刊论文
Pattern Recognition (PR), 2023, 卷号: 140, 页码: 109527
作者:  Weihan Chen;  Peisong Wang;  Jian Cheng
Adobe PDF(765Kb)  |  收藏  |  浏览/下载：119/38  |  提交时间：2023/06/20
Deep Neural Networks  Model Compression  Quantization  Pruning  
Optimization-Based Post-Training Quantization With Bit-Split and Stitching 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 2, 页码: 2119-2135
作者:  Wang, Peisong;  Chen, Weihan;  He, Xiangyu;  Chen, Qiang;  Liu, Qingshan;  Cheng, Jian
Adobe PDF(921Kb)  |  收藏  |  浏览/下载：206/60  |  提交时间：2023/03/20
Deep neural networks  compression  quantization  post-training quantization  
A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot 期刊论文
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2022, 卷号: 23, 期号: 8, 页码: 1217-1228
作者:  Tian, Manjun;  Li, Xiali;  Kong, Shihan;  Wu, Licheng;  Yu, Junzhi
收藏  |  浏览/下载：204/0  |  提交时间：2022/11/14
Object detection  Aquatic environment  Garbage cleaning robot  Modified YOLOv4  TP242  
Block Convolution: Toward Memory-Efficient Inference of Large-Scale CNNs on FPGA 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 5, 页码: 1436-1447
作者:  Li, Gang;  Liu, Zejian;  Li, Fanrong;  Cheng, Jian
Adobe PDF(4046Kb)  |  收藏  |  浏览/下载：290/31  |  提交时间：2022/06/10
Convolution  Field programmable gate arrays  System-on-chip  Task analysis  Random access memory  Tensors  Memory management  Block convolution  convolutional neural network (CNN) accelerator  field-programmable gate array (FPGA)  memory efficient  off-chip transfer  
Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA 期刊论文
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021, 期号: 2021.5, 页码: 1-1
作者:  Li, Gang;  Liu, Zejian;  Li, Fanrong;  Cheng, Jian
Adobe PDF(6174Kb)  |  收藏  |  浏览/下载：197/41  |  提交时间：2022/02/15
block convolution  memory-efficient  off-chip transfer  fpga  cnn accelerator  
Extremely Sparse Networks via Binary Augmented Pruning for Fast Image Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wang, Peisong;  Li, Fanrong;  Li, Gang;  Cheng, Jian
收藏  |  浏览/下载：210/0  |  提交时间：2022/01/27
Hardware acceleration  image classification  neural networks  pruning  software-hardware codesign  
ECBC: Efficient Convolution via Blocked Columnizing 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Zhao, Tianli;  Hu, Qinghao;  He, Xiangyu;  Xu, Weixiang;  Wang, Jiaxing;  Leng, Cong;  Cheng, Jian
Adobe PDF(3003Kb)  |  收藏  |  浏览/下载：309/36  |  提交时间：2022/01/27
Convolution  Tensors  Layout  Memory management  Indexes  Transforms  Performance evaluation  Convolutional neural networks (CNNs)  direct convolution  high performance computing for mobile devices  im2col convolution  memory-efficient convolution (MEC)  
FSA: A Fine-Grained Systolic Accelerator for Sparse CNNs 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2020, 卷号: 39, 期号: 11, 页码: 3589-3600
作者:  Li, Fanrong;  Li, Gang;  Mo, Zitao;  He, Xiangyu;  Cheng, Jian
Adobe PDF(1906Kb)  |  收藏  |  浏览/下载：349/63  |  提交时间：2021/01/06
Accelerator  architecture  convolutional neural networks (CNNs)  sparsity  
Bayesian Automatic Model Compression 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2020, 卷号: 14, 期号: 4, 页码: 727-736
作者:  Wang, Jiaxing;  Bai, Haoli;  Wu, Jiaxiang;  Cheng, Jian
Adobe PDF(1918Kb)  |  收藏  |  浏览/下载：306/58  |  提交时间：2020/12/04
Quantization  automatic machine learning  model compression  Bayes methods  Mathematical model  Training  Mixture models  Optimization  Machine learning  Bayesian learning  quantizartion  explainability