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» Non-parametric Mixture Models for Clustering
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83
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TMI
2008
136views more  TMI 2008»
14 years 9 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
15 years 4 months ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
ICASSP
2011
IEEE
14 years 1 months ago
Structural MAP adaptation in GMM-supervector based speaker recognition
In recent years, adaptation techniques have been given special focus in speaker recognition tasks, mainly targeting speaker and session variation disentangling under the Maximum a...
Marc Ferras, Koichi Shinoda, Sadaoki Furui
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
111
Voted
CIBCB
2007
IEEE
15 years 1 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao