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CVPR
2006
IEEE
14 years 7 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
13 years 12 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
BMCBI
2005
115views more  BMCBI 2005»
13 years 5 months ago
SUPERFICIAL - Surface mapping of proteins via structure-based peptide library design
Background: The determination of protein surfaces and the detection of binding sites are essential to our understanding of protein-protein interactions. Such binding sites can be ...
Andrean Goede, Ines S. Jaeger, Robert Preissner
CVPR
2009
IEEE
15 years 15 days ago
Epitomized Priors for Multi-labeling Problems
Image parsing remains difficult due to the need to combine local and contextual information when labeling a scene. We approach this problem by using the epitome as a prior over ...
Jonathan Warrell, Simon J. D. Prince, Alastair P. ...
ECCV
2004
Springer
14 years 7 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin