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检索条件"主题词=Multi-instance Multi-label Learning"
57 条 记 录,以下是31-40 订阅
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multi-instance multi-label learning based on Gaussian process with application to visual mobile robot navigation
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INFORMATION SCIENCES 2012年 190卷 162-177页
作者: He, Jianjun Gu, Hong Wang, Zhelong Dalian Univ Technol Fac Elect Informat & Elect Engn Dalian 116024 Liaoning Peoples R China
Classification problems have been frequently encountered in visual mobile robot navigation. The studies reported so far are mainly focused on the single label problem;i.e., each sample (datum) is assigned to a single ... 详细信息
来源: 评论
multi-instance multi-label learning
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ARTIFICIAL INTELLIGENCE 2012年 第1期176卷 2291-2320页
作者: Zhou, Zhi-Hua Zhang, Min-Ling Huang, Sheng-Jun Li, Yu-Feng Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210046 Jiangsu Peoples R China
In this paper, we propose the MIML (multi-instance multi-label learning) framework where an example is described by multiple instances and associated with multiple class labels. Compared to traditional learning framew... 详细信息
来源: 评论
multi-task MIML learning for pre-course student performance prediction
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Frontiers of Computer Science 2020年 第5期14卷 113-121页
作者: Yuling Ma Chaoran Cui Jun Yu Jie Guo Gongping Yang Yilong Yin School of Software Shandong UniversityJinan250100China School of Information Engineering Shandong Yingcai CollegeJinan250104China School of Computer Science and Technology Shandong University of Finance and EconomicsJinan250014China
In higher education,the initial studying period of each course plays a crucial role for students,and seriously influences the subsequent learning ***,given the large size of a course’s students at universities,it has... 详细信息
来源: 评论
ESRE: handling repeated entities in distant supervised relation extraction
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NEURAL COMPUTING & APPLICATIONS 2021年 第17期33卷 11325-11337页
作者: Sun, Xin Jiang, Jinghu Shang, Yuming Beijing Inst Technol Sch Comp Sci Beijing Peoples R China
Distant supervised relation extraction has been widely used to find novel relational facts from unstructured text. As far as we know, nearly all existing relation extraction models assume that each sentence contains p... 详细信息
来源: 评论
An Explainable multi-instance multi-label Classification Model for Full Slice Brain CT Images  3rd
An Explainable Multi-Instance Multi-Label Classification Mod...
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3rd IFAC Workshop pn Cyber-Physical and Human Systems (CPHS)
作者: Song, Changwei Fu, Guanghui Li, Jianqiang Pei, Yan Beijing Univ Technol Sch Software Engn Beijing 100124 Peoples R China Univ Aizu Comp Sci Div Aizu Wakamatsu Fukushima 9658580 Japan
Brain CT is the first choice for diagnosing intracranial diseases. However, the doctors who can accurate diagnosis is insufficient with the increasing number of patients. Nowadays, many computer-aided diagnosis algori... 详细信息
来源: 评论
Bayesian multi-instance multi-label learning using Gaussian process prior
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MACHINE learning 2012年 第1-2期88卷 273-295页
作者: He, Jianjun Gu, Hong Wang, Zhelong Dalian Univ Technol Fac Elect Informat & Elect Engn Dalian 116024 Liaoning Peoples R China
multi-instance multi-label learning (MIML) is a newly proposed framework, in which the multi-label problems are investigated by representing each sample with multiple feature vectors named instances. In this framework... 详细信息
来源: 评论
An Explainable multi-instance multi-label Classification Model for Full Slice Brain CT Images
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IFAC-PapersOnLine 2020年 第5期53卷 780-785页
作者: Changwei Song Guanghui Fu Jianqiang Li Yan Pei School of Software Engineering Beijing University of Technology Beijing 100124 China Computer Science Division University of Aizu Aizu-wakamatsu 965-8580 Japan
Brain CT is the first choice for diagnosing intracranial diseases. However, the doctors who can accurate diagnosis is insufficient with the increasing number of patients. Nowadays, many computer-aided diagnosis algori... 详细信息
来源: 评论
A Randomized Clustering Forest Approach for Efficient Prediction of Protein Functions
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IEEE ACCESS 2019年 7卷 12360-12372页
作者: Tang, Hong Wang, Yuanyuan Tang, Shaomin Chu, Dianhui Li, Chunshan Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510275 Guangdong Peoples R China Shenzhen Univ Coll Educ Shenzhen 518060 Peoples R China South China Univ Technol Sch Mech & Automot Engn Guangzhou 510630 Guangdong Peoples R China Harbin Inst Technol Dept Comp Sci Weihai 264209 Peoples R China
With the advances in genetic sequencing technology, the automated assignment of protein function has become a key challenge in bioinformatics and computational biology. In nature, many kinds of proteins consist of a v... 详细信息
来源: 评论
multi-instance multi-label distance metric learning for genome-wide protein function prediction
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COMPUTATIONAL BIOLOGY AND CHEMISTRY 2016年 63卷 30-40页
作者: Xu, Yonghui Min, Huaqing Song, Hengjie Wu, Qingyao South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Guangdong Peoples R China South China Univ Technol Sch Software Engn Guangzhou 510006 Guangdong Peoples R China
multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also m... 详细信息
来源: 评论
LEAP: learning to Prescribe Effective and Safe Treatment Combinations for multimorbidity  17
LEAP: Learning to Prescribe Effective and Safe Treatment Com...
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23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
作者: Zhang, Yutao Chen, Robert Tang, Jie Stewart, Walter F. Sun, Jimeng Tsinghua Univ Beijing Peoples R China Georgia Inst Technol Atlanta GA 30332 USA Sutter Hlth Sacramento CA USA
Managing patients with complex multimorbidity has long been recognized as a difficult problem due to complex disease and medication dependencies and the potential risk of adverse drug interactions. Existing work eithe... 详细信息
来源: 评论