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» Subspace Models for Functional MRI Data Analysis
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110
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ECML
2007
Springer
15 years 3 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
75
Voted
CVPR
2007
IEEE
15 years 4 months ago
Conformal Embedding Analysis with Local Graph Modeling on the Unit Hypersphere
We present the Conformal Embedding Analysis (CEA) for feature extraction and dimensionality reduction. Incorporating both conformal mapping and discriminating analysis, CEA projec...
Yun Fu, Ming Liu, Thomas S. Huang
ICIP
2000
IEEE
15 years 11 months ago
Clustered Component Analysis for FMRI Signal Estimation and Classification
In this paper, we introduce a method for estimating the statistically distinct neural responses in an sequence of functional magnetic resonance images (fMRI). The crux of our meth...
Charles A. Bouman, Sea Chen, Mark J. Lowe
CORR
2010
Springer
168views Education» more  CORR 2010»
14 years 8 months ago
Gaussian Process Structural Equation Models with Latent Variables
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
Ricardo Silva
83
Voted
TMI
2011
147views more  TMI 2011»
14 years 4 months ago
Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model
Abstract—Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements ...
Raja' S. Alomari, Jason J. Corso, Vipin Chaudhary