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ICML
2002
IEEE
14 years 8 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
CVPR
2007
IEEE
14 years 9 months ago
Moving Forward in Structure From Motion
It is well-known that forward motion induces a large number of local minima in the instantaneous least-squares reprojection error. This is caused in part by singularities in the e...
Andrea Vedaldi, Gregorio Guidi, Stefano Soatto
MVA
2007
160views Computer Vision» more  MVA 2007»
13 years 8 months ago
Probabilistic Motion Segmentation of Videos for Temporal Super Resolution
A novel scheme is proposed for achieving motion segmentation in low-frame rate videos, with application to temporal super resolution. Probabilistic generative models are commonly ...
Arasanathan Thayananthan, Masahiro Iwasaki, Robert...
NIPS
2007
13 years 8 months ago
Convex Relaxations of Latent Variable Training
We investigate a new, convex relaxation of an expectation-maximization (EM) variant that approximates a standard objective while eliminating local minima. First, a cautionary resu...
Yuhong Guo, Dale Schuurmans
IJCV
2010
158views more  IJCV 2010»
13 years 5 months ago
Metric Learning for Image Alignment
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
Minh Hoai Nguyen, Fernando De la Torre