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    MLMTA
    2007
    142views Machine Learning» more  MLMTA 2007»
    A Novel Hybrid Neural Network for Data Clustering
    13 years 9 months ago
    A Novel Hybrid Neural Network for Data Clustering
    Download  uclab.khu.ac.kr
    - Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised lea...
    Donghai Guan, Andrey Gavrilov, Weiwei Yuan, Young-...
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    ICIP
    2003
    IEEE
    207views Image Processing» more  ICIP 2003»
    Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
    14 years 9 months ago
    Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
    Download  www.vcipl.okstate.edu
    In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
    X. Song, G. Fan
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    EACL
    2006
    ACL Anthology
    94views Natural Language Processing» more  EACL 2006»
    Selecting the "Right" Number of Senses Based on Clustering Criterion Functions
    13 years 9 months ago
    Selecting the "Right" Number of Senses Based on Clustering Criterion Functions
    Download  www.d.umn.edu
    This paper describes an unsupervised knowledge
    Ted Pedersen, Anagha Kulkarni
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    ACL
    2008
    152views Computational Linguistics» more  ACL 2008»
    Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy
    13 years 9 months ago
    Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy
    Download  alice.nc.huji.ac.il
    We present a novel framework for the discovery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be ...
    Dmitry Davidov, Ari Rappoport
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    NIPS
    2008
    138views Information Technology» more  NIPS 2008»
    Learning Taxonomies by Dependence Maximization
    13 years 9 months ago
    Learning Taxonomies by Dependence Maximization
    Download  www.kyb.mpg.de
    We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
    Matthew B. Blaschko, Arthur Gretton
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