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JMLR
2011
148views more  JMLR 2011»
13 years 5 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
13 years 5 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
15 years 3 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 2 days 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 2 days 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...