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JMLR
2011
148views more  JMLR 2011»
14 years 4 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
SIAMJO
2011
14 years 4 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
ICCV
2009
IEEE
16 years 2 months ago
Efficient Discriminative Learning of Parts-based Models
Supervised learning of a parts-based model can be for- mulated as an optimization problem with a large (exponen- tial in the number of parts) set of constraints. We show how thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
CVPR
2005
IEEE
15 years 11 months ago
Dense Photometric Stereo Using a Mirror Sphere and Graph Cut
We present a surprisingly simple system that allows for robust normal reconstruction by dense photometric stereo, in the presence of severe shadows, highlight, transparencies, com...
Tai-Pang Wu, Chi-Keung Tang
CVPR
2007
IEEE
15 years 11 months ago
Autocalibration via Rank-Constrained Estimation of the Absolute Quadric
We present an autocalibration algorithm for upgrading a projective reconstruction to a metric reconstruction by estimating the absolute dual quadric. The algorithm enforces the ra...
Manmohan Krishna Chandraker, Sameer Agarwal, Fredr...