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ICASSP
2009
IEEE
13 years 6 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
ICA
2010
Springer
13 years 10 months ago
Blind Source Separation Based on Time-Frequency Sparseness in the Presence of Spatial Aliasing
In this paper, we propose a novel method for blind source separation (BSS) based on time-frequency sparseness (TF) that can estimate the number of sources and time-frequency masks,...
Benedikt Loesch, Bin Yang
ICML
2010
IEEE
13 years 10 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
IJNSEC
2006
71views more  IJNSEC 2006»
13 years 9 months ago
Joint Sparse Form of Window Three for Koblitz Curve
The joint sparse form (JSF) for the non-adjacent form (NAF) representation of two large integers a and b, was proposed by Solinas. Then Ciet extended it to the -JSF for the -NAF r...
Yong Ding, Kwok-Wo Wong, Yu-Min Wang
PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 7 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish