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» Multiple Kernel Learning with High Order Kernels
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ICML
2007
IEEE
14 years 8 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
IPMI
2005
Springer
14 years 8 months ago
Unified Statistical Approach to Cortical Thickness Analysis
This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of d...
Moo K. Chung, Steve Robbins, Alan C. Evans
ICML
2008
IEEE
14 years 8 months ago
Sparse multiscale gaussian process regression
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Bernhard Schölkopf, Christian Walder, Kwang I...
CF
2009
ACM
14 years 2 months ago
Wave field synthesis for 3D audio: architectural prospectives
In this paper, we compare the architectural perspectives of the Wave Field Synthesis (WFS) 3D-audio algorithm mapped on three different platforms: a General Purpose Processor (GP...
Dimitris Theodoropoulos, Catalin Bogdan Ciobanu, G...
NIPS
2004
13 years 9 months ago
Implicit Wiener Series for Higher-Order Image Analysis
The computation of classical higher-order statistics such as higher-order moments or spectra is difficult for images due to the huge number of terms to be estimated and interprete...
Matthias O. Franz, Bernhard Schölkopf