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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：41/15  |  提交时间：2024/05/30
Explanation  knowledge distillation  model compression  
Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning 期刊论文
BIOMIMETICS, 2024, 卷号: 9, 期号: 1, 页码: 19
作者:  Wang, Yu;  Wang, Jian;  Kang, Song;  Yu, Junzhi
Adobe PDF(1553Kb)  |  收藏  |  浏览/下载：69/12  |  提交时间：2024/03/26
biomimetic motion  biomimetic autonomous system  target following  deep reinforcement learning  predictive control  
A new super-predefined-time convergence and noise-tolerant RNN for solving time-variant linear matrix-vector inequality in noisy environment and its application to robot arm 期刊论文
NEURAL COMPUTING & APPLICATIONS, 2023, 页码: 17
作者:  Zheng, Boyu;  Yue, Chong;  Wang, Qianqian;  Li, Chunquan;  Zhang, Zhijun;  Yu, Junzhi;  Liu, Peter X.
收藏  |  浏览/下载：59/0  |  提交时间：2024/02/22
Linear matrix-vector inequality  Recurrent neural network  Robustness  Time-variant problem  Convergence  
A novel varying-parameter periodic rhythm neural network for solving time-varying matrix equation in finite energy noise environment and its application to robot arm 期刊论文
NEURAL COMPUTING & APPLICATIONS, 2023, 页码: 17
作者:  Li, Chunquan;  Zheng, Boyu;  Ou, Qingling;  Wang, Qianqian;  Yue, Chong;  Chen, Limin;  Zhang, Zhijun;  Yu, Junzhi;  Liu, Peter X.
收藏  |  浏览/下载：139/0  |  提交时间：2023/11/17
Zeroing neural network  Varying-parameter  Periodic rhythm  Time-varying matrix equation  Finite energy noise  
Large sequence models for sequential decision-making: a survey 期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2023, 卷号: 17, 期号: 6, 页码: 18
作者:  Wen, Muning;  Lin, Runji;  Wang, Hanjing;  Yang, Yaodong;  Wen, Ying;  Mai, Luo;  Wang, Jun;  Zhang, Haifeng;  Zhang, Weinan
Adobe PDF(1351Kb)  |  收藏  |  浏览/下载：142/3  |  提交时间：2023/11/17
sequential decision-making  sequence modeling  the Transformer  training system  
BSTG-Trans: A Bayesian Spatial-Temporal Graph Transformer for Long-term Pose Forecasting 期刊论文
IEEE Transactions on Multimedia, 2023, 卷号: Early Access, 期号: Early Access, 页码: Early Access
作者:  Shentong Mo;  Xin M(辛淼)
Adobe PDF(2209Kb)  |  收藏  |  浏览/下载：102/18  |  提交时间：2023/04/25
long-term forecasting  spatial-temporal graph transformer  Bayesian transformer  uncertainty estimation  
D-TNet: Category-Awareness Based Difference-Threshold Alternative Learning Network for Remote Sensing Image Change Detection 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 1-16
作者:  Wan, Ling;  Tian, Ye;  Kang, Wenchao;  Ma, Lei
Adobe PDF(8963Kb)  |  收藏  |  浏览/下载：143/37  |  提交时间：2023/03/20
Category-awareness  change detection  optical remote sensing image  threshold learning  
Global Instance Tracking: Locating Target More Like Humans 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 1, 页码: 576-592
作者:  Hu, Shiyu;  Zhao, Xin;  Huang, Lianghua;  Huang, Kaiqi
Adobe PDF(15055Kb)  |  收藏  |  浏览/下载：248/55  |  提交时间：2023/02/22
Global instance tracking  single object tracking  benchmark dataset  performance evaluation  human tracking ability  
Deep Reinforcement Learning With Part-Aware Exploration Bonus in Video Games 期刊论文
IEEE TRANSACTIONS ON GAMES, 2022, 卷号: 14, 期号: 4, 页码: 644-653
作者:  Xu, Pei;  Yin, Qiyue;  Zhang, Junge;  Huang, Kaiqi
Adobe PDF(1480Kb)  |  收藏  |  浏览/下载：331/83  |  提交时间：2023/02/22
Deep learning  exploration  reinforcement learning  video game  
A Brain-Inspired Approach for Probabilistic Estimation and Efficient Planning in Precision Physical Interaction 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 15
作者:  Xing, Dengpeng;  Yang, Yiming;  Zhang, Tielin;  Xu, Bo
Adobe PDF(2960Kb)  |  收藏  |  浏览/下载：228/12  |  提交时间：2022/06/10
Task analysis  Robots  Force  Planning  Mathematical models  Brain modeling  Biology  Brain-inspired structure  precision physical interaction  spiking neural networks (SNNs)