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ISCAS
2008
IEEE
169views Hardware» more  ISCAS 2008»
16 years 1 months ago
Sigma-delta learning for super-resolution independent component analysis
— Many source separation algorithms fail to deliver robust performance in presence of artifacts introduced by cross-channel redundancy, non-homogeneous mixing and highdimensional...
Amin Fazel, Shantanu Chakrabartty
235
Voted
TSP
2010
15 years 1 months ago
Optimization and analysis of distributed averaging with short node memory
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
VMV
2008
122views Visualization» more  VMV 2008»
15 years 8 months ago
Statistical analysis of Multi-Material Components using Dual Energy CT
This work describes a novel method for statistical analysis of multi-material components. The application scenario is industrial 3D X-ray computed tomography, emphasizing metrolog...
Christoph Heinzl, Johann Kastner, Torsten Möl...
195
Voted
IDA
2009
Springer
16 years 1 months ago
Estimating Squared-Loss Mutual Information for Independent Component Analysis
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
Taiji Suzuki, Masashi Sugiyama
CVPR
2009
IEEE
15 years 10 months ago
Nonlinear Nonnegative Component Analysis
In this paper general solutions for Nonlinear Nonnegative Component Analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonne...
Stefanos Zafeiriou, Maria Petrou