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» Nonlinear Component Analysis Based on Correntropy
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ESANN
2004
13 years 9 months ago
Separability of analytic postnonlinear blind source separation with bounded sources
The aim of blind source separation (BSS) is to transform a mixed random vector such that the original sources are recovered. If the sources are assumed to be statistically independ...
Fabian J. Theis, Peter Gruber
ICA
2004
Springer
14 years 28 days ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
IDA
2009
Springer
14 years 2 months ago
Learning Natural Image Structure with a Horizontal Product Model
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Urs Köster, Jussi T. Lindgren, Michael Gutman...
VLDB
2001
ACM
146views Database» more  VLDB 2001»
14 years 7 months ago
Combining multi-visual features for efficient indexing in a large image database
Abstract. The optimized distance-based access methods currently available for multidimensional indexing in multimedia databases have been developed based on two major assumptions: ...
Anne H. H. Ngu, Quan Z. Sheng, Du Q. Huynh, Ron Le...
JCP
2008
167views more  JCP 2008»
13 years 7 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao