The learned parametric mixture method is presented for a canonical cost function based ICA model on linear mixture, with several new findings. First, its adaptive algorithm is fu...
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of i...
Sangnam Nam, Michael E. Davies, Michael Elad, R&ea...
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
In this paper we present a new method of 3D non-negative tensor factorization (NTF) that is robust in the presence of noise and has many potential applications, including multi-way...
Andrzej Cichocki, Rafal Zdunek, Seungjin Choi, Rob...