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检索条件"机构=MIIT Key Laboratory of Pattern Analysis and Machine Intelligence"
228 条 记 录,以下是71-80 订阅
排序:
Incremental Multi-Label Learning with Active Queries
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Journal of Computer Science & Technology 2020年 第2期35卷 234-246页
作者: Sheng-Jun Huang Guo-Xiang Li Wen-Yu Huang Shao-Yuan Li College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Pattern Analysis and Machine Intelligence Ministry of Industry and Information Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing University Nanjing 210023China
In multi-label learning,it is rather expensive to label instances since they are simultaneously associated with multiple ***,active learning,which reduces the labeling cost by actively querying the labels of the most ... 详细信息
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Discrimination-Aware Domain Adversarial Neural Network
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Journal of Computer Science & Technology 2020年 第2期35卷 259-267页
作者: Yun-Yun Wang Jian-Min Gu Chao Wang Song-Can Chen Hui Xue College of Computer Science and Engineering Nanjing University of Posts and Telecommunications Nanjing 210046China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210046China College of Computer Science and Technology/College of Artificial Intelligence Nanjing University of Aeronautics and AstronauticsNanjing 210023China Key Laboratory of Pattern Analysis and Machine Intelligence Ministry of Industry and Information Technology Nanjing 210023China School of Computer Science and Engineering Southeast UniversityNanjing 210096China
The domain adversarial neural network(DANN)methods have been successfully proposed and attracted much attention *** DANNs,a discriminator is trained to discriminate the domain labels of features generated by a generat... 详细信息
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An Improved AdaBoost Method in Imbalanced Data Learning
An Improved AdaBoost Method in Imbalanced Data Learning
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Cyber-Physical Social intelligence (ICCSI), International Conference on
作者: Ting Li Xiaofeng Chen Weikai Li Department of Mathematics Chongqing Jiaotong University Chongqing China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing China
Learning from imbalanced datasets has recently received increasing research attention. Despite the remarkable results of AdaBoost in balanced situation, the imbalance problem remains to be solved. To address this, thi...
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A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising
arXiv
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arXiv 2021年
作者: Wen, Chao Xu, Miao Zhang, Zhilin Zheng, Zhenzhe Wang, Yuhui Liu, Xiangyu Rong, Yu Xie, Dong Tan, Xiaoyang Yu, Chuan Xu, Jian Wu, Fan Chen, Guihai Zhu, Xiaoqiang Zheng, Bo MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China Shanghai Jiao Tong University China Alibaba Group China
In online advertising, auto-bidding has become an essential tool for advertisers to optimize their preferred ad performance metrics by simply expressing high-level campaign objectives and constraints. Previous works d... 详细信息
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Cross-Subject Data Splitting for Brain-to-Text Decoding
arXiv
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arXiv 2023年
作者: Yin, Congchi Yu, Qian Fang, Zhiwei He, Jie Peng, Changping Lin, Zhangang Shao, Jingping Li, Piji Nanjing University of Aeronautics and Astronautics China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing China *** Beijing China
Recent major milestones have successfully decoded non-invasive brain signals (e.g. functional Magnetic Resonance Imaging (fMRI) and electroencephalogram (EEG)) into natural language. Despite the progress in model desi... 详细信息
来源: 评论
Greedy-Step Off-Policy Reinforcement Learning
arXiv
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arXiv 2021年
作者: Wang, Yuhui Wu, Qingyuan He, Pengcheng Tan, Xiaoyang College of Computer Science and Technology Nanjing University of Aeronautics Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China
Most of the policy evaluation algorithms are based on the theories of Bellman Expectation and Optimality Equation, which derive two popular approaches - Policy Iteration (PI) and Value Iteration (VI). However, multi-s... 详细信息
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Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
arXiv
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arXiv 2023年
作者: Wang, Xinrui Wan, Wenhai Geng, Chuanxin Li, Shaoyuan Chen, Songcan College of Computer Science and Technology Nanjing University of Aeronautics Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China
Learning binary classifiers from positive and unlabeled data (PUL) is vital in many real-world applications, especially when verifying negative examples is difficult. Despite the impressive empirical performance of re... 详细信息
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Medical Report Generation based on Segment-Enhanced Contrastive Representation Learning
arXiv
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arXiv 2023年
作者: Zhao, Ruoqing Wang, Xi Dai, Hongliang Gao, Pan Li, Piji College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China
Automated radiology report generation has the potential to improve radiology reporting and alleviate the workload of radiologists. However, the medical report generation task poses unique challenges due to the limited... 详细信息
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A Systematic Evaluation of Large Language Models for Natural Language Generation Tasks
arXiv
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arXiv 2024年
作者: Ni, Xuanfan Li, Piji College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China
Recent efforts have evaluated large language models (LLMs) in areas such as commonsense reasoning, mathematical reasoning, and code generation. However, to the best of our knowledge, no work has specifically investiga... 详细信息
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A Survey on Incomplete Multi-label Learning: Recent Advances and Future Trends
arXiv
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arXiv 2024年
作者: Li, Xiang Liu, Jiexi Wang, Xinrui Chen, Songcan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence China
In reality, data often exhibit associations with multiple labels, making multi-label learning (MLL) become a prominent Copyright © 2024, The Authors. All rights reserved.
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