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Collective Movement Simulation: Methods and Applications 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 452-480
作者:  Hua Wang;  Xing-Yu Guo;  Hao Tao;  Ming-Liang Xu
Adobe PDF(1439Kb)  |  收藏  |  浏览/下载：23/7  |  提交时间：2024/05/23
Collective movement simulation, multiple objects, multiple discipline, simulation effect, collective intelligence  
Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 411-430
作者:  Qiyue Yin;  Tongtong Yu;  Shengqi Shen;  Jun Yang;  Meijing Zhao;  Wancheng Ni;  Kaiqi Huang;  Bin Liang;  Liang Wang
Adobe PDF(2923Kb)  |  收藏  |  浏览/下载：22/9  |  提交时间：2024/05/23
Deep reinforcement learning, distributed machine learning, self-play, population-play, toolbox  
Text Difficulty Study: Do Machines Behave the Same as Humans Regarding Text Difficulty? 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 283-293
作者:  Bowen Chen;  Xiao Ding;  Yi Zhao;  Bo Fu;  Tingmao Lin;  Bing Qin;  Ting Liu
Adobe PDF(1796Kb)  |  收藏  |  浏览/下载：31/5  |  提交时间：2024/04/23
Cognition inspired natural language processing, psycholinguistics, explainability, text difficulty, curriculum learning  
A Comprehensive Overview of CFN From a Commonsense Perspective 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 239-256
作者:  Ru Li;  Yunxiao Zhao;  Zhiqiang Wang;  Xuefeng Su;  Shaoru Guo;  Yong Guan;  Xiaoqi Han;  Hongyan Zhao
Adobe PDF(2392Kb)  |  收藏  |  浏览/下载：22/7  |  提交时间：2024/04/23
Chinese FrameNet (CFN), commonsense, scenario commonsense, frame, knowledge  
Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 89-103
作者:  Chaojie Wu;  Mingyang Li;  Ying Gao;  Xinyan Xie;  Wing W. Y. Ng;  Ahmad Musyafa
Adobe PDF(7319Kb)  |  收藏  |  浏览/下载：24/10  |  提交时间：2024/04/23
Weakly supervised object localization, erasing method, deep learning, computer vision, art authentication and copyright protection