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» Multiple Kernel Learning with High Order Kernels
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CVPR
2009
IEEE
15 years 2 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic
WSCG
2003
318views more  WSCG 2003»
13 years 9 months ago
Quality Issues of Hardware-Accelerated High-Quality Filtering on PC Graphics Hardware
This paper summarizes several quality issues of an approach for high-quality filtering with arbitrary filter kernels on PC graphics hardware that has been presented previously. ...
Markus Hadwiger, Helwig Hauser, Torsten Mölle...
ESANN
2008
13 years 9 months ago
GeoKernels: modeling of spatial data on geomanifolds
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
Alexei Pozdnoukhov, Mikhail F. Kanevski
CVPR
2012
IEEE
11 years 10 months ago
2D/3D rotation-invariant detection using equivariant filters and kernel weighted mapping
In many vision problems, rotation-invariant analysis is necessary or preferred. Popular solutions are mainly based on pose normalization or brute-force learning, neglecting the in...
Kun Liu, Qing Wang, Wolfgang Driever, Olaf Ronnebe...
PAMI
2006
117views more  PAMI 2006»
13 years 7 months ago
Metric Learning for Text Documents
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
Guy Lebanon