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检索条件"机构=Computer Science with Artificial Intelligence and Machine Learning"
2811 条 记 录,以下是2701-2710 订阅
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L1-Norm-Based 2DLPP
L1-Norm-Based 2DLPP
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2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
作者: Hao-Xin Zhao Hong-Jie Xing Xi-Zhao Wang Jun-Fen Chen Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China
In this paper, we propose a new L1-Norm-Based two-dimensional locality preserving projections (2DLPP-L1). Traditional 2D-LPP can preserve local structure and extract feature directly form matrices, which shows great a... 详细信息
来源: 评论
Regional objects based image retrieval
Regional objects based image retrieval
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2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
作者: Jian-Guo Wu Xi-Zhao Wang Hong-Jie Xing Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China
Content-based image retrieval has become an important research area. In order to extract the semantic information within the user’s query concept, we propose an image retrieval method based on regional objects. It is... 详细信息
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Fostering Collaborative Work between educators in higher education
Fostering Collaborative Work between educators in higher edu...
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IEEE International Conference on Systems, Man and Cybernetics
作者: Dulce Mota Carlos Vaz de Carvalho Luis Paulo Reis GILT-Graphics Interaction and Learning Technologies School of Engineering Polytechnic of Porto Porto Portugal FEUP-Faculty of Engineering LIAAC-Artificial Intelligence and Computer Science Laboratory University of Porto Porto Portugal
This paper presents the architecture that supports the collaborative model ACEM (Advanced Collaborative Educational Model) to assist educators in the collaborative design of learning activities, supported by a high-le... 详细信息
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A conceptual model for collaborative learning activities design
A conceptual model for collaborative learning activities des...
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IEEE Education Engineering (EDUCON)
作者: Dulce Mota Carlos Vaz de Carvalho Luis Paulo Reis GILT Graphics Interaction and Learning Technologies Institute of Engineering Polytechnic of Porto Porto Portugal FEUP Faculty of Engineering LIAAC Artificial Intelligence and Computer Science Lab University of Porta Porto Portugal
This paper presents the Advanced Collaborative Educational Model (ACEM) for conception of collaborative learning activities. It is based on collaboration between teachers through virtual interactions, reutilization, i... 详细信息
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Open Review in computer science Elsevier grand challenge on executable papers
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Procedia computer science 2011年 4卷 778-780页
作者: Y.-A. Le Borgne A. Campo Computational Modeling Laboratory and Electronics and Informatics Dpt. Vrije Universiteit Brussel Pleinlaan 2 1050 - Brussels - Belgium Machine Learning Group Computer Science Department Universit́e Libre de Bruxelles Bd Triomphe 1050 - Brussels - Belgium IRIDIA Artificial Intelligence Laboratory Universit́e Libre de Bruxelles 50 Av. F. Roosevelt CP 194/6 1050 - Brussels - Belgium
We present Open Review, a web-based platform aimed at stimulating executable papers by means of post-publication peer-review. Its goal is to bring computer science researchers to collaboratively build their work upon ... 详细信息
来源: 评论
Reports of the AAAI 2010 spring symposia
Reports of the AAAI 2010 spring symposia
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作者: Barkowsky, Thomas Bertel, Sven Broz, Frank Chaudhri, Vinay K. Eagle, Nathan Genesereth, Michael Halpin, Harry Hamner, Emily Hoffmann, Gabe Hölscher, Christoph Horvitz, Eric Lauwers, Tom McGuinness, Deborah L. Michalowski, Marek Mower, Emily Shipley, Thomas F. Stubbs, Kristen Vogl, Roland Williams, Mary-Anne Cognitive Systems Group University of Bremen Research Center SFB/TR 8 Spatial Cognition Germany Human Factors Division Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign IL United States Adaptive Systems Research Group Computer Science Department University of Hertfordshire United Kingdom Artificial Intelligence Center at SRI International United States Txteagle Inc. MIT Media Laboratory United States Computer Science Department Stanford University United States University of Edinburgh United Kingdom Robotics Institute Carnegie Mellon University United States Palo Alto Research Center United States Center for Cognitive Science University of Freiburg Germany CREATE lab Carnegie Mellon Robotics Institute United States Rensselaer Polytechnic Institute United States University of Southern California United States Department of Psychology Temple University Spatial Intelligence and Learning Center United States IRobot Corporation United States Stanford Program in Law Science and Technology Stanford University Law School United States Innovation and Enterprise Research Laboratory University of Technology Sydney Australia
The Association for the Advancement of artificial intelligence, in cooperation with Stanford University's Department of computer science, presented the 2010 Spring Symposium Series Monday through Wednesday, March ... 详细信息
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Selection of deep web database based on retrieval performance
Selection of deep web database based on retrieval performanc...
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2nd International Workshop on Education Technology and computer science, ETCS 2010
作者: Li, Weijing Yuan, Fang Zhang, Ming Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding Hebei China
A mass of high-quality information included in Deep Web can be accessed, which is still growing rapidly with the rapid development of the World Wide Web. Therefore it becomes more and more important to find the Web da... 详细信息
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A survey on active learning strategy
A survey on active learning strategy
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International Conference on machine learning and Cybernetics
作者: Sun, Li-Li Wang, Xi-Zhao Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China
Active learning is a hot topic in machine learning field. The main task of active learning is to automatically select the representative instances for efficiently reducing the sample complexity. This paper presents a ... 详细信息
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Potential support vector machine based on the reduced samples
Potential support vector machine based on the reduced sample...
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International Conference on Information science and Engineering
作者: Lu, Shu-Xia Cao, Gui-En Meng, Jie Wang, Hua-Chao Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding Hebei China
When the training dataset is very large, the learning process of potential support vector machine takes up so large memory that the training speed is very slow. To accelerate the training speed of the potential suppor... 详细信息
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Support vector machine based on a new reduced samples method
Support vector machine based on a new reduced samples method
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International Conference on machine learning and Cybernetics
作者: Lu, Shu-Xia Meng, Jie Cao, Gui-En Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China
The support vectors play an important role in the training to find the optimal hyper-plane. For the problem of many non-support vectors and a few support vectors in the classification of SVM, a method to reduce the sa... 详细信息
来源: 评论