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» Dyad Ranking Using A Bilinear Plackett-Luce Model
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SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
13 years 11 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
FCSC
2007
159views more  FCSC 2007»
13 years 5 months ago
Ranking with uncertain labels and its applications
1 The techniques for image analysis and classi cation generally consider the image sample labels xed and without uncertainties. The rank regression problem is studied in this pape...
Shuicheng Yan, Huan Wang, Jianzhuang Liu, Xiaoou T...
IBPRIA
2009
Springer
13 years 10 months ago
Large Scale Online Learning of Image Similarity through Ranking
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
CVPR
2008
IEEE
14 years 7 months ago
Spectrally optimal factorization of incomplete matrices
From the recovery of structure from motion to the separation of style and content, many problems in computer vision have been successfully approached by using bilinear models. The...
Pedro M. Q. Aguiar, João M. F. Xavier, Mark...