Sciweavers

IJCNN
2007
IEEE
13 years 10 months ago
Sparse Distributed Representations for Words with Thresholded Independent Component Analysis
— We show that independent component analysis (ICA) can be used to find distributed representations for words that can be further processed by thresholding to produce sparse rep...
Jaakko J. Väyrynen, Lasse Lindqvist, Timo Hon...
CEC
2007
IEEE
13 years 11 months ago
Constrained genetic algorithm based independent component analysis
Independent Component Analysis, a computationally efficient statistical signal processing technique, has been an area of interest for researchers for many practical applications in...
D. P. Acharya, Ganapati Panda, Y. V. S. Lakshmi
ICASSP
2008
IEEE
13 years 11 months ago
An ICA-based multilinear algebra tools for dimensionality reduction in hyperspectral imagery
Dimensionality reduction (DR) is a major issue to improve the efficiency of the classifiers in Hyperspectral images (HSI). Recently, the independent component analysis (ICA) app...
Nadine Renard, Salah Bourennane
IDA
2009
Springer
13 years 11 months ago
Learning Natural Image Structure with a Horizontal Product Model
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Urs Köster, Jussi T. Lindgren, Michael Gutman...
IDA
2009
Springer
13 years 11 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
ACML
2009
Springer
13 years 11 months ago
Estimating Likelihoods for Topic Models
Abstract. Topic models are a discrete analogue to principle component analysis and independent component analysis that model topic at the word level within a document. They have ma...
Wray L. Buntine
ICASSP
2009
IEEE
13 years 11 months ago
Independent component analysis for noisy speech recognition
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
Hsin-Lung Hsieh, Jen-Tzung Chien, Koichi Shinoda, ...
ISBI
2009
IEEE
13 years 11 months ago
EEG Classification by ICA Source Selection of Laplacian-Filtered Data
We studied the performance of a double-spatial filtering method for classification of single-trial electroencephalography (EEG) data that couples the spherical surface Laplacian...
Claudio Carvalhaes, Marcos Perreau Guimaraes, Loga...
ICPR
2004
IEEE
14 years 5 months ago
Learning High-level Independent Components of Images through a Spectral Representation
Statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. Here we extend these methods for le...
Aapo Hyvärinen, Jussi T. Lindgren
ICPR
2006
IEEE
14 years 5 months ago
ICA-Based Clustering for Resolving Permutation Ambiguity in Frequency-Domain Convolutive Source Separation
Permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. In this pape...
Minje Kim, Seungjin Choi