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» Nonlinear Component Analysis Based on Correntropy
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NIPS
2007
13 years 9 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
DAC
2005
ACM
14 years 8 months ago
A non-parametric approach for dynamic range estimation of nonlinear systems
It has been widely recognized that the dynamic range information of an application can be exploited to reduce the datapath bitwidth of either processors or ASICs, and therefore th...
Bin Wu, Jianwen Zhu, Farid N. Najm
TIP
2011
162views more  TIP 2011»
13 years 2 months ago
Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
Allan Aasbjerg Nielsen
NIPS
2003
13 years 9 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou
PR
2007
145views more  PR 2007»
13 years 7 months ago
Face recognition using a kernel fractional-step discriminant analysis algorithm
Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
Guang Dai, Dit-Yan Yeung, Yuntao Qian