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A Multi-Task MRC Framework for Chinese Emotion Cause and Experiencer Extraction 会议论文
, Bratislava, Slovakia, 2021-09
作者:  Haoda Qian;  Qiudan Li;  Zaichuan Tang
Adobe PDF(79001Kb)  |  收藏  |  浏览/下载：363/126  |  提交时间：2022/06/14
Multi-target Coverage with Connectivity Maintenance using Knowledge-incorporated Policy Framework 会议论文
, Xi'an China, May 31-Jun. 4
作者:  Shiguang Wu;  Zhiqiang Pu;  Zhen Liu;  Tenghai Qiu;  Jianqiang Yi;  Tianle Zhang
Adobe PDF(12862Kb)  |  收藏  |  浏览/下载：293/48  |  提交时间：2022/04/06
Robust Cross-lingual Task-oriented Dialogue 期刊论文
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2021, 卷号: 20, 期号: 6, 页码: 24
作者:  Xiang, Lu;  Zhu, Junnan;  Zhao, Yang;  Zhou, Yu;  Zong, Chengqing
Adobe PDF(1935Kb)  |  收藏  |  浏览/下载：304/71  |  提交时间：2021/12/28
Cross-lingual  dialogue system  adversarial learning  knowledge  robustness  
Computing Paradigms in Emerging Vehicular Environments: A Review 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 3, 页码: 491-511
作者:  Lion Silva;  Naercio Magaia;  Breno Sousa;  Anna Kobusińska;  António Casimiro;  Constandinos X. Mavromoustakis;  George Mastorakis;  Victor Hugo C. de Albuquerque
Adobe PDF(12933Kb)  |  收藏  |  浏览/下载：135/23  |  提交时间：2021/04/09
Computing paradigm  cloud  edge  fog  internet of vehicle (IoV)  vehicular networks  
Data-Based Optimal Tracking of Autonomous Nonlinear Switching Systems 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 1, 页码: 227-238
作者:  Xiaofeng Li;  Lu Dong;  Changyin Sun
Adobe PDF(2830Kb)  |  收藏  |  浏览/下载：212/53  |  提交时间：2021/04/09
Adaptive dynamic programming  approximation error  data-based control  Q-learning  switching system  
Evolving Container to Unikernel for Edge Computing and Applications in Process Industry 期刊论文
PROCESSES, 2021, 卷号: 9, 期号: 2, 页码: 18
作者:  Chen, Shichao;  Zhou, Mengchu
Adobe PDF(619Kb)  |  收藏  |  浏览/下载：266/56  |  提交时间：2021/03/29
big data analytics  lightweight virtualization  cloud computing  edge computing  industrial process  Industry 4.0  Internet of things  machine learning  process industry  fault diagnosis