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    GFKL
    2005
    Springer
    144views Data Mining» more  GFKL 2005»
    Visual Mining in Music Collections
    14 years 1 months ago
    Visual Mining in Music Collections
    Download  www.mybytes.de
    We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Visualization based on perceptually motivated audio features and Emer...
    Fabian Mörchen, Alfred Ultsch, Mario Nöc...
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    ENGL
    2007
    180views more  ENGL 2007»
    Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
    13 years 7 months ago
    Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
    Download  www.engineeringletters.com
    — The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
    Shreyas Sen, Seetharam Narasimhan, Amit Konar
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    KDD
    2004
    ACM
    237views Data Mining» more  KDD 2004»
    Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
    14 years 8 months ago
    Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
    Download  www.eh3.uc.edu
    Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
    Mario Medvedovic, Junhai Guo
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    SPEECH
    1998
    118views more  SPEECH 1998»
    Dimensionality reduction of electropalatographic data using latent variable models
    13 years 7 months ago
    Dimensionality reduction of electropalatographic data using latent variable models
    Download  faculty.ucmerced.edu
    We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
    Miguel Á. Carreira-Perpiñán, ...
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    SDM
    2004
    SIAM
    218views Data Mining» more  SDM 2004»
    Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
    13 years 9 months ago
    Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
    Download  www.riacs.edu
    This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
    Ashok N. Srivastava
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