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    NIPS
    2003
    137views Information Technology» more  NIPS 2003»
    Online Passive-Aggressive Algorithms
    13 years 10 months ago
    Online Passive-Aggressive Algorithms
    Download  jmlr.csail.mit.edu
    We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
    Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...
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    NIPS
    2003
    141views Information Technology» more  NIPS 2003»
    Salient Boundary Detection using Ratio Contour
    13 years 10 months ago
    Salient Boundary Detection using Ratio Contour
    Download  books.nips.cc
    This paper presents a novel graph-theoretic approach, named ratio contour, to extract perceptually salient boundaries from a set of noisy boundary fragments detected in real image...
    Song Wang, Toshiro Kubota, Jeffrey Mark Siskind
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    NIPS
    2003
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    When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts?
    13 years 10 months ago
    When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts?
    Download  www.stanford.edu
    We interpret non-negative matrix factorization geometrically, as the problem of finding a simplicial cone which contains a cloud of data points and which is contained in the posi...
    David L. Donoho, Victoria Stodden
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    NIPS
    2003
    168views Information Technology» more  NIPS 2003»
    A Sampled Texture Prior for Image Super-Resolution
    13 years 10 months ago
    A Sampled Texture Prior for Image Super-Resolution
    Download  books.nips.cc
    Super-resolution aims to produce a high-resolution image from a set of one or more low-resolution images by recovering or inventing plausible high-frequency image content. Typical...
    Lyndsey C. Pickup, Stephen J. Roberts, Andrew Ziss...
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    NIPS
    2003
    144views Information Technology» more  NIPS 2003»
    Warped Gaussian Processes
    13 years 10 months ago
    Warped Gaussian Processes
    Download  books.nips.cc
    We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
    Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
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