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ICASSP
2011
IEEE
13 years 13 days ago
Estimation of cortical connectivity from E/MEG using nonlinear state-space models
We present the problem of estimating cortical connectivity between different regions of the cortex from scalp electroencephalographic (EEG) or magnetoencephalographic (MEG) data a...
Bing Leung, Patrick Cheung, Barry D. Van Veen
HUMO
2007
Springer
14 years 2 months ago
Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking
In this paper, we suggest to model priors on human motion by means of nonparametric kernel densities. Kernel densities avoid assumptions on the shape of the underlying distribution...
Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-...
ML
2006
ACM
121views Machine Learning» more  ML 2006»
13 years 8 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
ESANN
2007
13 years 10 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley
NIPS
2001
13 years 10 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger