86 search results - page 12 / 18 » Approximation of Gaussian process regression models after tr... |
101
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ICASSP
2011
IEEE
14 years 3 months ago
2011
IEEE
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
JCNS
2010
14 years 10 months ago
2010
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
ICML
2005
IEEE
16 years 17 days ago
2005
IEEE
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
131
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TSP
2010
14 years 6 months ago
2010
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
111
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KDD
2000
ACM
15 years 3 months ago
2000
ACM
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...