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    NC
    2006
    132views Neural Networks» more  NC 2006»
    Learning short multivariate time series models through evolutionary and sparse matrix computation
    13 years 8 months ago
    Learning short multivariate time series models through evolutionary and sparse matrix computation
    Download  bura.brunel.ac.uk
    Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
    Stephen Swift, Joost N. Kok, Xiaohui Liu
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    ICASSP
    2008
    IEEE
    139views Signal Processing» more  ICASSP 2008»
    Subspace compressive detection for sparse signals
    14 years 3 months ago
    Subspace compressive detection for sparse signals
    Download  www.ece.udel.edu
    The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
    Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
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    MLDM
    2007
    Springer
    143views Machine Learning» more  MLDM 2007»
    Nonlinear Feature Selection by Relevance Feature Vector Machine
    14 years 3 months ago
    Nonlinear Feature Selection by Relevance Feature Vector Machine
    Download  www.nec-labs.com
    Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
    Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
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    AAAI
    2010
    169views Intelligent Agents» more  AAAI 2010»
    Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
    13 years 9 months ago
    Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
    Download  www.stat.berkeley.edu
    Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
    Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bi...
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    TNN
    2010
    143views Management» more  TNN 2010»
    Using unsupervised analysis to constrain generalization bounds for support vector classifiers
    13 years 3 months ago
    Using unsupervised analysis to constrain generalization bounds for support vector classifiers
    Download  www.smartlab.dibe.unige.it
    Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
    Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
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