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检索条件"机构=Lab of Data Science and Intelligence Application"
71 条 记 录,以下是21-30 订阅
排序:
label Distribution Learning Based on Two-stage Model Error Repair Method
Label Distribution Learning Based on Two-stage Model Error R...
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IEEE International Symposium on Information (IT) in Medicine and Education, ITME
作者: Yu Mao Zhiyi Cai Yulin Li Chunyu Shi School of Computer Science Minnan Normal University Zhangzhou China Lab of Data Science and Intelligence Application Minnan Normal University Zhangzhou China
label distribution learning (LDL) is a new learning paradigm proposed in the field of machine learning to solve the problem of label ambiguity. Many existing label distribution learning algorithms only consider the si...
来源: 评论
Multi-label Feature Selection Based on Improved Fisher Score with label Correlation
Multi-Label Feature Selection Based on Improved Fisher Score...
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IEEE International Symposium on Information (IT) in Medicine and Education, ITME
作者: Yu Mao Yuxuan Cheng Chunyu Shi Yaojin Lin School of Computer Science Minnan Normal University Zhangzhou China Lab of Data Science and Intelligence Application Minnan Normal University Zhangzhou China
Feature selection for multi-label classification has received extensive attention in the fields of machine learning and data mining. However, some feature selection methods fail to incorporate label correlations, resu...
来源: 评论
CoCGAN: Contrastive Learning for Adversarial Category Text Generation  29
CoCGAN: Contrastive Learning for Adversarial Category Text G...
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29th International Conference on Computational Linguistics, COLING 2022
作者: Sheng, Xin Xu, Linli Xu, Yinlong Bao, Changcun Chen, Huang Ren, Bo Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China China School of Computer Science and Technology University of Science and Technology of China China State Key Laboratory of Cognitive Intelligence China Tencent Youtu Lab China
The task of generating texts of different categories has attracted more and more attention in the area of natural language generation recently. Meanwhile, generative adversarial net (GAN) has demonstrated its effectiv... 详细信息
来源: 评论
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design
arXiv
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arXiv 2023年
作者: Zhang, Zaixi Liu, Qi Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China China State Key Laboratory of Cognitive Intelligence China
Generating molecules with high binding affinities to target proteins (a.k.a. structure-based drug design) is a fundamental and challenging task in drug discovery. Recently, deep generative models have achieved remarka... 详细信息
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FEDGT: FEDERATED NODE CLASSIFICATION WITH SCAlabLE GRAPH TRANSFORMER
arXiv
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arXiv 2024年
作者: Zhang, Zaixi Hu, Qingyong Yu, Yang Gao, Weibo Liu, Qi Anhui Province Key Lab of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China China State Key Laboratory of Cognitive Intelligence Anhui Hefei China Hong Kong University of Science and Technology Hong Kong
Graphs are widely used to model relational data. As graphs are getting larger and larger in real-world scenarios, there is a trend to store and compute subgraphs in multiple local systems. For example, recently propos... 详细信息
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OFHR: Online Streaming Feature Selection With Hierarchical Structure Based on Relief  11
OFHR: Online Streaming Feature Selection With Hierarchical S...
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11th International Conference on Information Technology in Medicine and Education, ITME 2021
作者: Wang, Chenxi Zhang, Xiaoqing Chen, Jinkun Mao, Yu Li, Shaozi Lin, Yaojin Minnan Normal University School of Computer Science Lab of Data Science and Intelligence Application Zhangzhou China Minnan Normal University School of Mathematics and Statistics Zhangzhou China Xiamen University Department of Artificial Intelligence Xiamen China
Hierarchical classification learning, an emerging classification task in machine learning, is an essential topic. In which various feature selection algorithms have been proposed to select informative features for hie... 详细信息
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Resource Reservation Contract Design for Mobile Edge Computing with Energy Harvesting  23
Resource Reservation Contract Design for Mobile Edge Computi...
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Proceedings of the 4th International Conference on Artificial intelligence and Computer Engineering
作者: Deyue Jiang Liming Chen Ziqiong Lin Wenjie Zhang Yifeng Zheng Key lab of data science and intelligence application School of Computer Sciences Minnan Normal University China Zhangzhou Affiliated Hospital of Fujian Medical University China School of Computer Sciences Minnan Normal University China
To address the bottleneck of energy performance, this paper considers an energy harvesting (EH)-enabled Mobile Edge Computing (MEC) system with contract users (CUs) and random users (RUs). The resource demands of CUs ...
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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison
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IEEE/CAA Journal of Automatica Sinica 2023年 第4期10卷 957-968页
作者: Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China
Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the... 详细信息
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Hierarchical Streaming Feature Selection Based on FDAF-score
Hierarchical Streaming Feature Selection Based on FDAF-score
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IEEE International Symposium on Information (IT) in Medicine and Education, ITME
作者: Zhuoxin He Yu Mao Yixiang Zeng Xiehua Yu Yaojin Lin School of Computer Science Lab of Data Science and Intelligence Application Minnan Normal University Zhangzhou China School of Computer and Information Minnan Science and Technology University Quanzhou China
In many practical classification scenarios, the data label space has a hierarchical structure, these data often have high-dimensional features, and there are irrelevant and redundant features. Thus, a variety of hiera... 详细信息
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Backdoor Defense via Deconfounded Representation Learning
Backdoor Defense via Deconfounded Representation Learning
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Zaixi Zhang Qi Liu Zhicai Wang Zepu Lu Qingyong Hu Anhui Province Key Lab of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China State Key Laboratory of Cognitive Intelligence Hefei Anhui China University of Science and Technology of China Hong Kong University of Science and Technology
Deep neural networks (DNNs) are recently shown to be vulnerable to backdoor attacks, where attackers embed hidden backdoors in the DNN model by injecting a few poisoned examples into the training dataset. While extens...
来源: 评论