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ECSQARU
2005
Springer
14 years 2 months ago
Default Clustering from Sparse Data Sets
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
Julien Velcin, Jean-Gabriel Ganascia
ICONIP
2007
13 years 10 months ago
Sparse Super Symmetric Tensor Factorization
In the paper we derive and discuss a wide class of algorithms for 3D Super-symmetric nonnegative Tensor Factorization (SNTF) or nonnegative symmetric PARAFAC, and as a special case...
Andrzej Cichocki, Marko Jankovic, Rafal Zdunek, Sh...
ICASSP
2010
IEEE
13 years 3 months ago
Temporally constrained SCA with applications to EEG data
In this paper we propose an iterative algorithm for solving the problem of extracting a sparse source signal when a reference signal for the desired source signal is available. In...
Nasser Mourad, James P. Reilly, Gary Hasey, Duncan...
DCC
2008
IEEE
14 years 8 months ago
On solving sparse algebraic equations over finite fields
A system of algebraic equations over a finite field is called sparse if each equation depends on a small number of variables. Finding efficiently solutions to the system is an unde...
Igor Semaev
ICA
2007
Springer
14 years 19 days ago
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
David Knowles, Zoubin Ghahramani