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    » Robustness Analysis of the Neural Gas Learning Algorithm
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    TSE
    2010
    197views more  TSE 2010»
    A Genetic Algorithm-Based Stress Test Requirements Generator Tool and Its Empirical Evaluation
    13 years 2 months ago
    A Genetic Algorithm-Based Stress Test Requirements Generator Tool and Its Empirical Evaluation
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    Genetic algorithms (GAs) have been applied previously to UML-driven, stress test requirements generation with the aim of increasing chances of discovering faults relating to networ...
    Vahid Garousi
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    COLING
    2008
    128views Computational Linguistics» more  COLING 2008»
    Robust and Efficient Chinese Word Dependency Analysis with Linear Kernel Support Vector Machines
    13 years 9 months ago
    Robust and Efficient Chinese Word Dependency Analysis with Linear Kernel Support Vector Machines
    Download  www.aclweb.org
    Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...
    Yu-Chieh Wu, Jie-Chi Yang, Yue-Shi Lee
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    CIBCB
    2007
    IEEE
    204views Computational Biology» more  CIBCB 2007»
    Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
    13 years 11 months ago
    Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
    Download  www.jihe.net
    Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
    Ji He, Xinbin Dai, Xuechun Zhao
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    ICCV
    2001
    IEEE
    136views Computer Vision» more  ICCV 2001»
    Robust Principal Component Analysis for Computer Vision
    14 years 9 months ago
    Robust Principal Component Analysis for Computer Vision
    Download  www.cs.brown.edu
    Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
    Fernando De la Torre, Michael J. Black
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    NIPS
    1997
    96views Information Technology» more  NIPS 1997»
    Learning Generative Models with the Up-Propagation Algorithm
    13 years 8 months ago
    Learning Generative Models with the Up-Propagation Algorithm
    Download  hebb.mit.edu
    Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
    Jong-Hoon Oh, H. Sebastian Seung
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