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    PAMI
    2008
    135views more  PAMI 2008»
    MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
    14 years 9 months ago
    MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
    Download  parnec.nuaa.edu.cn
    In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
    Zhe Wang, Songcan Chen, Tingkai Sun
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    81
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    IRMA
    2000
    112views Information Technology» more  IRMA 2000»
    Recognizing bounds of context change in on-line learning
    14 years 11 months ago
    Recognizing bounds of context change in on-line learning
    Download  www.cs.jyu.fi
    The on-line algorithms in machine learning are intended to discover unknown function of the domain based on incremental observing of it instance by instance. These algorithms have...
    Helen Kaikova, Vagan Y. Terziyan, Borys Omelayenko
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    80
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    FLAIRS
    2003
    187views Artificial Intelligence» more  FLAIRS 2003»
    Algorithms for Large Scale Markov Blanket Discovery
    14 years 11 months ago
    Algorithms for Large Scale Markov Blanket Discovery
    Download  www.aaai.org
    This paper presents a number of new algorithms for discovering the Markov Blanket of a target variable T from training data. The Markov Blanket can be used for variable selection ...
    Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
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    ESANN
    2000
    177views Neural Networks» more  ESANN 2000»
    Algorithmic approaches to training Support Vector Machines: a survey
    14 years 11 months ago
    Algorithmic approaches to training Support Vector Machines: a survey
    Download  www.iipl.fudan.edu.cn
    : Support Vector Machines (SVMs) have become an increasingly popular tool for machine learning tasks involving classi cation, regression or novelty detection. They exhibit good gen...
    Colin Campbell
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    SDM
    2009
    SIAM
    225views Data Mining» more  SDM 2009»
    Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
    15 years 6 months ago
    Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
    Download  siam.org
    Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
    Fei Wang, Chris H. Q. Ding, Tao Li
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