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» Extractive summarization using a latent variable model
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ICA
2007
Springer
14 years 22 days ago
Supervised and Semi-supervised Separation of Sounds from Single-Channel Mixtures
In this paper we describe a methodology for model-based single channel separation of sounds. We present a sparse latent variable model that can learn sounds based on their distribu...
Paris Smaragdis, Bhiksha Raj, Madhusudana V. S. Sh...
KDD
2009
ACM
207views Data Mining» more  KDD 2009»
14 years 7 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
SPEECH
1998
118views more  SPEECH 1998»
13 years 6 months ago
Dimensionality reduction of electropalatographic data using latent variable models
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
Miguel Á. Carreira-Perpiñán, ...
ICASSP
2011
IEEE
12 years 10 months ago
An extension of the ICA model using latent variables
The Independent Component Analysis (ICA) model is extended to the case where the components are not necessarily independent: depending on the value a hidden latent process at the ...
Selwa Rafi, Marc Castella, Wojciech Pieczynski
MLMI
2007
Springer
14 years 21 days ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...