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面向认知的多源数据学习理论和算法研究进展
Research Progress on Cognitive-Oriented Multi-Source Data Learning Theory and Algorithm

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杨柳 1   于剑 2 *   刘烨 3   詹德川 4  
文摘 多源数据学习在大数据时代具有极其重要的意义.目前,多源数据学习算法研究远远超前于多源数据学习理论研究,经典的机器学习理论难以应用于多源数据学习,更难以提供多源数据学习算法在实际应用中的理论保障.从学习的最终目的是知识这一认知切入点出发,对人类学习的认知机理、机器学习的三大经典理论(计算学习理论、统计学习理论和概率图理论)以及多源数据学习算法设计这3个方面的研究进展进行总结,最后给出未来研究方向的思考.
其他语种文摘 In the age of big data, learning from multi-source data plays an important role in many real applications. To date, plenty of multi-source data learning algorithms have been proposed, however, they pay little attention to the fundamental theoretic laws. Meanwhile, it is hard for the classical machine learning theories to govern all learning systems, and to further provide a theoretical support for multi-source learning algorithms. From the perspective of knowledge acquisition through learning, a survey is given on the research progress of three key problems: the human cognitive mechanism, three classical machine learning theories (such as computational learning theory, statistical learning theory, and probabilistic graphical model), and the design of multi-source learning algorithms. Future theoretical research issues of multi-source data learning also presented and investigated.
来源 软件学报 ,2017,28(11):2971-2991 【核心库】
DOI 10.13328/j.cnki.jos.005348
关键词 统计学习理论 ; 模式分类 ; 特征空间 ; 认知心理
地址

1. 天津大学计算机科学与技术学院, 天津, 300350  

2. 北京交通大学, 交通数据分析与挖掘北京市重点实验室, 北京, 100044  

3. 中国科学院心理研究所, 脑与认知科学国家重点实验室, 北京, 100101  

4. 南京大学, 计算机软件新技术国家重点实验室, 江苏, 南京, 210023

语种 中文
文献类型 研究性论文
ISSN 1000-9825
学科 自动化技术、计算机技术
基金 国家自然科学基金
文献收藏号 CSCD:6105819

参考文献 共 202 共11页

1.  . Nature. Big data,2008 被引 2    
2.  . Science. Special online collection: Dealing with data,2011 被引 2    
3.  Silver D. Mastering the game of Go with deep neural networks and tree search. Nature,2016,529(7587):484-489 被引 654    
4.  . http://www.aaai.org/Conferences/AAAI/2016/aaai16speakers.php#Hassabis 被引 1    
5.  Cowie R. Emotion recognition in human-computer interaction. IEEE Signal Processing Magazine,2001,18(1):32-80 被引 45    
6.  Cohen I. Semisupervised learning of classifiers: Theory, algorithms and their applications to human- computer interaction. IEEE Trans. on Pattern Analysis and Machine Intelligence,2004,26(12):1553-1567 被引 10    
7.  Bekkerman R. Multi-Modal clustering for multimedia collections. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition,2007:1-8 被引 1    
8.  Wang J. A multimodal scheme for program segmentation and representation in broadcast video streams. IEEE Trans. on Multimedia,2008,10(3):393-408 被引 1    
9.  Cristani M. Audio-Visual event recognition in surveillance video sequences. IEEE Trans, on Multimedia,2007,9(2):257-267 被引 4    
10.  Liu J. Video search re-ranking via multi-graph propagation. Proc. of the 15th ACM Int'l Conf. on Multimedia,2007:208-217 被引 1    
11.  Valiant L. A theory of the learnable. Communications of the ACM,1984,27(11):1134-1142 被引 95    
12.  Cortes C. Support vector networks. Machine Learning,1995,20(3):273-297 被引 2232    
13.  Kleinberg J. An impossibility theorem for clustering. Proc. of the Advances in Neural Information Processing Systems,2003:463-470 被引 1    
14.  Valiant L. Probably approximately correct: Nature's Algorithms for Leaning and Prospering in a Complex World,2013 被引 1    
15.  Pearl J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference,1988 被引 91    
16.  Pavlas J. Searching for the algorithms underlying life. Quanta Magazine,2016 被引 1    
17.  Snedeker J. Word learning. Encyclopedia of Neuroscience,2009:503-508 被引 1    
18.  Urcuioli P J. Associative concept learning in animals: Issues and opportunities. Journal of the Experimental Analysis of Behavior,2014,101(1):165-170 被引 2    
19.  Daniel T A. Temporal dynamics of task switching and abstract-concept learning in pigeons. Front Psychol,2015,6:1-8 被引 1    
20.  Gingras G. The differing impact of multisensory and unisensory integration on behavior. Journal of Neuroscience,2009,29(15):4897-4902 被引 1    
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