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» The Construction of Smooth Models using Irregular Embeddings...
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NCA
2002
IEEE
13 years 7 months ago
The Construction of Smooth Models using Irregular Embeddings Determined by a Gamma Test Analysis
One of the key problems in forming a smooth model from input-output data is the determination of which input variables are relevant in predicting a given output. In this paper we ...
Alban P. M. Tsui, Antonia J. Jones, A. Guedes de O...
SBRN
2000
IEEE
13 years 11 months ago
Non-Linear Modelling and Chaotic Neural Networks
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
Antonia J. Jones, Steve Margetts, Peter Durrant, A...
DIS
2007
Springer
14 years 1 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...
BMCBI
2008
177views more  BMCBI 2008»
13 years 7 months ago
Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis
Background: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of b...
Yuanxin Xi, David M. Rocke