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    STOC
    2009
    ACM
    145views Algorithms» more  STOC 2009»
    Finding, minimizing, and counting weighted subgraphs
    14 years 8 months ago
    Finding, minimizing, and counting weighted subgraphs
    Download  www.math.ias.edu
    d Abstract] Virginia Vassilevska School of Mathematics Institute for Advanced Study Princeton, NJ 08540 USA virgi@math.ias.edu Ryan Williams School of Mathematics Institute for Adv...
    Virginia Vassilevska, Ryan Williams
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    KDD
    2009
    ACM
    191views Data Mining» more  KDD 2009»
    Efficient methods for topic model inference on streaming document collections
    14 years 8 months ago
    Efficient methods for topic model inference on streaming document collections
    Download  www.cs.umass.edu
    Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
    Limin Yao, David M. Mimno, Andrew McCallum
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    KDD
    2007
    ACM
    167views Data Mining» more  KDD 2007»
    Generalized component analysis for text with heterogeneous attributes
    14 years 7 months ago
    Generalized component analysis for text with heterogeneous attributes
    Download  www.cs.umass.edu
    We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...
    Xuerui Wang, Chris Pal, Andrew McCallum
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    FOCS
    2008
    IEEE
    119views Theoretical Computer Science» more  FOCS 2008»
    Dynamic Connectivity: Connecting to Networks and Geometry
    14 years 1 months ago
    Dynamic Connectivity: Connecting to Networks and Geometry
    Download  people.csail.mit.edu
    Dynamic connectivity is a well-studied problem, but so far the most compelling progress has been confined to the edge-update model: maintain an understanding of connectivity in a...
    Timothy M. Chan, Mihai Patrascu, Liam Roditty
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    ESANN
    2006
    262views Neural Networks» more  ESANN 2006»
    Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
    13 years 8 months ago
    Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
    Download  www.dice.ucl.ac.be
    Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
    Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
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