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ICA
2004
Springer
16 years 19 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
LWA
2007
15 years 8 months ago
Parameter Learning for a Readability Checking Tool
This paper describes the application of machine learning methods to determine parameters for DeLite, a readability checking tool. DeLite pinpoints text segments that are difficul...
Tim vor der Brück, Johannes Leveling
CVPR
2001
IEEE
16 years 9 months ago
Issues on the Geometry of Central Catadioptric Image Formation
An imaging system with a single effective viewpoint is called a central projection system. The conventional perspective camera is an example of a central projection system. System...
João P. Barreto, Helder Araújo
CVPR
2005
IEEE
16 years 9 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
ICCV
2007
IEEE
16 years 9 months ago
Semi-supervised Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Deng Cai, Xiaofei He, Jiawei Han