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NECO
2002
104views more  NECO 2002»
13 years 7 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
NECO
2007
95views more  NECO 2007»
13 years 7 months ago
Support Vector Ordinal Regression
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal...
Wei Chu, S. Sathiya Keerthi
NECO
2007
90views more  NECO 2007»
13 years 7 months ago
Neighborhood Property-Based Pattern Selection for Support Vector Machines
Support Vector Machine (SVM) has been spotlighted in the machine learning community thanks to its theoretical soundness and practical performance. When applied to a large data set...
Hyunjung Shin, Sungzoon Cho
NECO
2007
152views more  NECO 2007»
13 years 7 months ago
3D Periodic Human Motion Reconstruction from 2D Motion Sequences
In this report, we present and evaluate a method of reconstructing three-dimensional (3D) periodic human motion from two-dimensional (2D) motion sequences. Based on a Fourier deco...
Zonghua Zhang, Nikolaus F. Troje
NECO
2007
51views more  NECO 2007»
13 years 7 months ago
Models Wagging the Dog: Are Circuits Constructed with Disparate Parameters?
In a recent paper Prinz et al. (Nature Neurosci. 7, 1345-52 (2004)) have addressed the fundamental question, whether neural systems are built with a fixed blueprint of tightly con...
Thomas Nowotny, Attila Szücs, Rafael Levi, Al...