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    » Denoising and Untangling Graphs Using Degree Priors
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    NIPS
    2003
    124views Information Technology» more  NIPS 2003»
    Denoising and Untangling Graphs Using Degree Priors
    14 years 11 months ago
    Denoising and Untangling Graphs Using Degree Priors
    Download  books.nips.cc
    This paper addresses the problem of untangling hidden graphs from a set of noisy detections of undirected edges. We present a model of the generation of the observed graph that in...
    Quaid Morris, Brendan J. Frey
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    ICONIP
    2009
    132views Information Technology» more  ICONIP 2009»
    A Bayesian Graph Clustering Approach Using the Prior Based on Degree Distribution
    14 years 7 months ago
    A Bayesian Graph Clustering Approach Using the Prior Based on Degree Distribution
    Download  www-als.ics.nitech.ac.jp
    Naoyuki Harada, Yuta Ishikawa, Ichiro Takeuchi, Ry...
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    ICMLA
    2009
    184views Machine Learning» more  ICMLA 2009»
    Exact Graph Structure Estimation with Degree Priors
    14 years 7 months ago
    Exact Graph Structure Estimation with Degree Priors
    Download  www1.cs.columbia.edu
    We describe a generative model for graph edges under specific degree distributions which admits an exact and efficient inference method for recovering the most likely structure. T...
    Bert Huang, Tony Jebara
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    ICPR
    2008
    IEEE
    252views Computer Vision» more  ICPR 2008»
    Continuous graph cuts for prior-based object segmentation
    15 years 10 months ago
    Continuous graph cuts for prior-based object segmentation
    Download  ipa.iwr.uni-heidelberg.de
    In this paper we propose a novel prior-based variational object segmentation method in a global minimization framework which unifies image segmentation and image denoising. The id...
    Anders Heyden, Christian Gosch, Christoph Schn&oum...
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    PAMI
    2008
    198views more  PAMI 2008»
    A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
    14 years 9 months ago
    A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
    Download  research.microsoft.com
    Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
    Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
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