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    SDM
    2011
    SIAM
    284views Data Mining» more  SDM 2011»
    The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
    13 years 1 months ago
    The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
    Download  cs.stanford.edu
    While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomp...
    Myunghwan Kim 0002, Jure Leskovec
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    SDM
    2011
    SIAM
    414views Data Mining» more  SDM 2011»
    Clustered low rank approximation of graphs in information science applications
    13 years 1 months ago
    Clustered low rank approximation of graphs in information science applications
    Download  www.cs.utexas.edu
    In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
    Berkant Savas, Inderjit S. Dhillon
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    SDM
    2011
    SIAM
    243views Data Mining» more  SDM 2011»
    Data Integration via Constrained Clustering: An Application to Enzyme Clustering
    13 years 1 months ago
    Data Integration via Constrained Clustering: An Application to Enzyme Clustering
    Download  www.cs.rpi.edu
    When multiple data sources are available for clustering, an a priori data integration process is usually required. This process may be costly and may not lead to good clusterings,...
    Elisa Boari de Lima, Raquel Cardoso de Melo Minard...
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    SDM
    2011
    SIAM
    256views Data Mining» more  SDM 2011»
    Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
    13 years 1 months ago
    Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
    Download  michael.hahsler.net
    This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
    Michael Hahsler, Margaret H. Dunham
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    SDM
    2011
    SIAM
    233views Data Mining» more  SDM 2011»
    Distributed Monitoring of the R2 Statistic for Linear Regression
    13 years 1 months ago
    Distributed Monitoring of the R2 Statistic for Linear Regression
    Download  www.cs.umbc.edu
    The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more depe...
    Kanishka Bhaduri, Kamalika Das, Chris Giannella
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    SDM
    2011
    SIAM
    233views Data Mining» more  SDM 2011»
    Multi-Instance Mixture Models
    13 years 1 months ago
    Multi-Instance Mixture Models
    Download  www.datalab.uci.edu
    Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
    James R. Foulds, Padhraic Smyth
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    SDM
    2011
    SIAM
    232views Data Mining» more  SDM 2011»
    A Sequential Dual Method for Structural SVMs
    13 years 1 months ago
    A Sequential Dual Method for Structural SVMs
    Download  www.keerthis.com
    In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
    Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
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    SDM
    2011
    SIAM
    218views Data Mining» more  SDM 2011»
    Segmented nestedness in binary data
    13 years 1 months ago
    Segmented nestedness in binary data
    Download  www.cs.helsinki.fi
    A binary matrix is fully nested if its columns form a chain of subsets; that is, any two columns are ordered by the subset relation, where we view each column as a subset of the r...
    Esa Junttila, Petteri Kaski
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    SDM
    2011
    SIAM
    242views Data Mining» more  SDM 2011»
    Fast Algorithms for Finding Extremal Sets
    13 years 1 months ago
    Fast Algorithms for Finding Extremal Sets
    Download  www.bayardo.org
    Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
    Roberto J. Bayardo, Biswanath Panda
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    SDM
    2011
    SIAM
    198views Data Mining» more  SDM 2011»
    Exemplar-based Robust Coherent Biclustering
    13 years 1 months ago
    Exemplar-based Robust Coherent Biclustering
    Download  www.cs.iastate.edu
    The biclustering, co-clustering, or subspace clustering problem involves simultaneously grouping the rows and columns of a data matrix to uncover biclusters or sub-matrices of the...
    Kewei Tu, Xixiu Ouyang, Dingyi Han, Vasant Honavar
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