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ICA
2007
Springer
14 years 1 months ago
Subspaces of Spatially Varying Independent Components in fMRI
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
Jarkko Ylipaavalniemi, Ricardo Vigário
ISBI
2008
IEEE
14 years 8 months ago
Improved fMRI group studies based on spatially varying non-parametric BOLD signal modeling
Multi-subject analysis of functional Magnetic Resonance Imaging (fMRI) data relies on within-subject studies, which are usually conducted using a massively univariate approach. In...
Philippe Ciuciu, Thomas Vincent, Anne-Laure Fouque...
ANOR
2002
93views more  ANOR 2002»
13 years 7 months ago
Cutting and Surrogate Constraint Analysis for Improved Multidimensional Knapsack Solutions
We use surrogate analysis and constraint pairing in multidimensional knapsack problems to fix some variables to zero and to separate the rest into two groups
Maria A. Osorio, Fred Glover, Peter Hammer
VL
2007
IEEE
132views Visual Languages» more  VL 2007»
14 years 1 months ago
A Study on Applying Roles of Variables in Introductory Programming
Expert programmers possess programming knowledge, which is language independent and abstract. Still, programming is mostly taught only via constructs of a programming language and...
Pauli Byckling, Jorma Sajaniemi
ICPR
2000
IEEE
14 years 8 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes