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TIT
2008
141views more  TIT 2008»
15 years 1 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli
TSP
2010
14 years 7 months ago
Optimal/near-optimal dimensionality reduction for distributed estimation in homogeneous and certain inhomogeneous scenarios
We consider distributed estimation of a deterministic vector parameter from noisy sensor observations in a wireless sensor network (WSN). The observation noise is assumed uncorrela...
Jun Fang, Hongbin Li
ESANN
2004
15 years 2 months ago
Dimensionality reduction and classification using the distribution mapping exponent
: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...
Marcel Jirina
ICML
2005
IEEE
16 years 1 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
ICA
2004
Springer
15 years 6 months ago
Non-linear ICA by Using Isometric Dimensionality Reduction
In usual ICA methods, sources are typically estimated by maximizing a measure of their statistical independence. This paper explains how to perform non-linear ICA by preprocessing ...
John Aldo Lee, Christian Jutten, Michel Verleysen