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TIT
2008
141views more  TIT 2008»
14 years 10 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
95
Voted
TSP
2010
14 years 4 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
86
Voted
ESANN
2004
14 years 11 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
96
Voted
ICML
2005
IEEE
15 years 11 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
88
Voted
ICA
2004
Springer
15 years 3 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