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JMLR
2010
155views more  JMLR 2010»
13 years 2 months ago
Bayesian Gaussian Process Latent Variable Model
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Michalis Titsias, Neil D. Lawrence

Book
996views
15 years 5 months ago
The Scientist and Engineer's Guide to Digital Signal Processing
"The world of science and engineering is filled with signals: images from remote space probes, voltages generated by the heart and brain, radar and sonar echoes, seismic vibra...
Steve Smith
NN
2008
Springer
129views Neural Networks» more  NN 2008»
13 years 8 months ago
Neurolinguistic approach to natural language processing with applications to medical text analysis
Brain processes responsible for understanding language are approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not ...
Wlodzislaw Duch, Pawel Matykiewicz, John Pestian
GEOS
2005
Springer
14 years 1 months ago
Processes and Events in Dynamic Geo-Networks
Traditional spatial information systems hold only a single state of the ‘real world’. However, geographic phenomena have not only static but dynamic characteristics. The work d...
Antony Galton, Michael F. Worboys
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 6 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava