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ICA
2004
Springer
14 years 22 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
CORR
2011
Springer
172views Education» more  CORR 2011»
13 years 2 months ago
Possibilities and impossibilities in Kolmogorov complexity extraction
Randomness extraction is the process of constructing a source of randomness of high quality from one or several sources of randomness of lower quality. The problem can be modeled ...
Marius Zimand
IWPC
2009
IEEE
14 years 2 months ago
Natural language parsing for fact extraction from source code
We present a novel approach to extract structural information from source code using state-of-the-art parser technologies for natural languages. The parser technology is robust in...
Jens Nilsson, Welf Löwe, Johan Hall, Joakim N...
ESANN
2004
13 years 8 months ago
Robust overcomplete matrix recovery for sparse sources using a generalized Hough transform
We propose an algorithm for recovering the matrix A in X = AS where X is a random vector of lower dimension than S. S is assumed to be sparse in the sense that S has less nonzero e...
Fabian J. Theis, Pando G. Georgiev, Andrzej Cichoc...
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Extraction of semantic biomedical relations from text using conditional random fields
Background: The increasing amount of published literature in biomedicine represents an immense source of knowledge, which can only efficiently be accessed by a new generation of a...
Markus Bundschus, Mathäus Dejori, Martin Stet...