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NIPS
2001
13 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ADCM
2008
136views more  ADCM 2008»
13 years 10 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
PAMI
2007
125views more  PAMI 2007»
13 years 9 months ago
Matching by Linear Programming and Successive Convexification
—We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. M...
Hao Jiang, Mark S. Drew, Ze-Nian Li
CVPR
2011
IEEE
13 years 6 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman
DAGM
2011
Springer
12 years 10 months ago
Using Landmarks as a Deformation Prior for Hybrid Image Registration
Hybrid registration schemes are a powerful alternative to fully automatic registration algorithms. Current methods for hybrid registration either include the landmark information a...
Marcel Lüthi, Christoph Jud, Thomas Vetter