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检索条件"机构=Intelligent Computing & Machine Learning Lab"
75 条 记 录,以下是61-70 订阅
排序:
Stock volatility prediction using recurrent neural networks with sentiment analysis
arXiv
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arXiv 2017年
作者: Liu, Yifan Qin, Zengchang Li, Pengyu Wan, Tao Intelligent Computing and Machine Learning Lab School of ASEE Beihang University Beijing100191 School of Mechanical Engineering and Automation Beihang University Beijing100191 School of Biological Science and Medical Engineering Beihang University Beijing100191 China
In this paper, we propose a model to analyze sentiment of online stock forum and use the information to predict the stock volatil-ity in the Chinese market. We have labeled the sentiment of the online financial posts ... 详细信息
来源: 评论
Prior Visual Relationship Reasoning For Visual Question Answering
Prior Visual Relationship Reasoning For Visual Question Answ...
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IEEE International Conference on Image Processing
作者: Zhuoqian Yang Zengchang Qin Jing Yu Tao Wan Robotics Institute Carnegie Mellon University Pittsburgh PA USA Intelligent Computing and Machine Learning Lab School of ASEE Beihang University China Institute of Information Engineering CAS China School of Biological Science and Medical Engineering Beihang University Beijing China
Visual Question Answering (VQA) is a representative task of cross-modal reasoning where an image and a free-form question in natural language are presented and the correct answer needs to be determined using both visu... 详细信息
来源: 评论
Double variance reduction: a smoothing trick for composite optimization problems without first-order gradient  24
Double variance reduction: a smoothing trick for composite o...
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Proceedings of the 41st International Conference on machine learning
作者: Hao Di Haishan Ye Yueling Zhang Xiangyu Chang Guang Dai Ivor W. Tsang Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China and SGIT AI Lab State Grid Corporation of China International Business School Beijing Foreign Studies University Beijing China Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China SGIT AI Lab State Grid Corporation of China CFAR and IHPC Agency for Science Technology and Research (A*STAR) Singapore and College of Computing and Data Science NTU Singapore
Variance reduction techniques are designed to decrease the sampling variance, thereby accelerating convergence rates of first-order (FO) and zeroth-order (ZO) optimization methods. However, in composite optimization p...
来源: 评论
A novel texture image segmentation model based on multi-scale structure
A novel texture image segmentation model based on multi-scal...
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International Conference on Multisensor Fusion and Integration for intelligent Systems (MFI)
作者: Hai Min Xiao-Feng Wang De-Shuang Huang Department of Automation University of Science and Technology of China Hefei Anhui China Intelligent Computing Lab Chinese Academy of Sciences Department of Computer Science and Technology Hefei University Hefei Anhui China Machine Learning and Systems Biology Laboratory Tongji University Shanghai China
Using neighborhood information from different scales in an effective way for object segmentation, however, remains a difficult problem. In this paper, we propose a novel method which incorporates the multi-scale struc... 详细信息
来源: 评论
DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue
arXiv
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arXiv 2020年
作者: Jiang, Xiaoze Yu, Jing Sun, Yajing Qin, Zengchang Zhu, Zihao Hu, Yue Wu, Qi Institute of Information Engineering Chinese Academy of Sciences Beijing China Intelligent Computing and Machine Learning Lab School of ASEE Beihang University Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China AI Research Codemao Inc University of Adelaide Australia
Visual Dialogue task requires an agent to be engaged in a conversation with human about an image. The ability of generating detailed and non-repetitive responses is crucial for the agent to achieve human-like conversa... 详细信息
来源: 评论
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
arXiv
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arXiv 2024年
作者: Di, Hao Ye, Haishan Zhang, Yueling Chang, Xiangyu Dai, Guang Tsang, Ivor W. Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China SGIT AI Lab State Grid Corporation of China China International Business School Beijing Foreign Studies University Beijing China Singapore College of Computing and Data Science NTU Singapore
Variance reduction techniques are designed to decrease the sampling variance, thereby accelerating convergence rates of first-order (FO) and zeroth-order (ZO) optimization methods. However, in composite optimization p... 详细信息
来源: 评论
Can Gaussian sketching converge faster on a preconditioned landscape?  24
Can Gaussian sketching converge faster on a preconditioned l...
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Proceedings of the 41st International Conference on machine learning
作者: Yilong Wang Haishan Ye Guang Dai Ivor W. Tsang Center for Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University China and SGIT AI Lab State Grid Corporation of China SGIT AI Lab State Grid Corporation of China CFAR and IHPC Agency for Science Technology and Research (A*STAR) Singapore and College of Computing and Data Science NTU Singapore
This paper focuses on the large-scale optimization which is very popular in the big data era. The gradient sketching is an important technique in the large-scale optimization. Specifically, the random coordinate desce...
来源: 评论
Emotion classification with data augmentation using generative adversarial networks
arXiv
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arXiv 2017年
作者: Zhu, Xinyue Liu, Yifan Qin, Zengchang Li, Jiahong School of Electronic Engineering Bejing University of Posts and Telecommunications Beijing100876 China Intelligent Computing and Machine Learning Lab School of ASEE Beihang University Beijing100191 China Beijing San Kuai Yun Technology Co. Ltd. Hengdian Building No.4 Wangjing East RD Chaoyang District Beijing China
It is a difficult task to classify images with multiple class labels using only a small number of labeled examples, especially when the label (class) distribution is imbalanced. Emotion classification is such an examp... 详细信息
来源: 评论
Tackling Instance-Dependent label Noise via a Universal Probabilistic Model
arXiv
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arXiv 2021年
作者: Wang, Qizhou Han, Bo Liu, Tongliang Niu, Gang Yang, Jian Gong, Chen Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of MoE School of Computer Science and Engineering Nanjing University of Science and Technology China Department of Computer Science Hong Kong Baptist University Hong Kong Trustworthy Machine Learning Lab School of Computer Science Faculty of Engineering The University of Sydney Australia Japan Department of Computing Hong Kong Polytechnic University Hong Kong
The drastic increase of data quantity often brings the severe decrease of data quality, such as incorrect label annotations, which poses a great challenge for robustly training Deep Neural Networks (DNNs). Existing le... 详细信息
来源: 评论
Preface
Advanced Topics in Science and Technology in China
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Advanced Topics in Science and Technology in China 2014年 vii页
作者: Qin, Zengchang Tang, Yongchuan Intelligent Computing and Machine Learning Lab School of ASEE Beihang University Beijing China College of Computer Science Zhejiang University HangzhouZhejiang China
来源: 评论