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    TKDE
    2010
    224views more  TKDE 2010»
    Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
    13 years 1 days ago
    Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
    Download  www.cs.wayne.edu
    Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
    Yanhua Chen, Lijun Wang, Ming Dong
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    SDM
    2004
    SIAM
    225views Data Mining» more  SDM 2004»
    Active Semi-Supervision for Pairwise Constrained Clustering
    13 years 6 months ago
    Active Semi-Supervision for Pairwise Constrained Clustering
    Download  www.cs.utexas.edu
    Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
    Sugato Basu, Arindam Banerjee, Raymond J. Mooney
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    SDM
    2007
    SIAM
    176views Data Mining» more  SDM 2007»
    Adaptive Concept Learning through Clustering and Aggregation of Relational Data
    13 years 6 months ago
    Adaptive Concept Learning through Clustering and Aggregation of Relational Data
    Download  siam.org
    We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
    Hichem Frigui, Cheul Hwang
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    BIOCOMP
    2007
    161views Bioinformatics» more  BIOCOMP 2007»
    Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
    13 years 6 months ago
    Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
    Download  www.biomedcentral.com
    The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
    Cole Harris, Noushin Ghaffari
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    AAAI
    2010
    154views Intelligent Agents» more  AAAI 2010»
    Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
    13 years 6 months ago
    Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
    Download  research.microsoft.com
    Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
    Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...
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