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» On fields of nonlinear regression models
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NECO
1998
168views more  NECO 1998»
13 years 7 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson
ICMCS
2010
IEEE
194views Multimedia» more  ICMCS 2010»
13 years 7 months ago
Speech emotion estimation in 3D space
Speech processing is an important aspect of affective computing. Most research in this direction has focused on classifying emotions into a small number of categories. However, nu...
Dongrui Wu, Thomas D. Parsons, Emily Mower, Shrika...
CGF
2005
252views more  CGF 2005»
13 years 7 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
UAI
2000
13 years 9 months ago
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
ICNC
2009
Springer
14 years 2 months ago
Estimating Strength of Concrete Using a Grammatical Evolution
The main purpose of this paper is to propose an incorporating a grammatical evolution (GE) into the genetic algorithm (GA), called GEGA, and apply it to estimate the compressive s...
Hsun-Hsin Hsu, Li Chen, Chang-Huan Kou, Tai-Sheng ...