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QEST
2005
IEEE
14 years 2 months ago
An approximation algorithm for labelled Markov processes: towards realistic approximation
Abstract— Approximation techniques for labelled Markov processes on continuous state spaces were developed by Desharnais, Gupta, Jagadeesan and Panangaden. However, it has not be...
Alexandre Bouchard-Côté, Norm Ferns, ...
ICTAI
2005
IEEE
14 years 2 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
ICASSP
2009
IEEE
14 years 13 days ago
Dirichlet process mixture models with multiple modalities
The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters o...
John William Paisley, Lawrence Carin
HICSS
2006
IEEE
89views Biometrics» more  HICSS 2006»
14 years 2 months ago
Towards Creative Environments: Conclusions from Creative Space
In recent papers and a book [1], [2], we have investigated diverse types of knowledge creation processes based on the concept of Creative Space (a metamodel of knowledge creation ...
Andrzej P. Wierzbicki, Yoshiteru Nakamori
JMLR
2010
112views more  JMLR 2010»
13 years 3 months ago
Sparse Spectrum Gaussian Process Regression
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
Miguel Lázaro-Gredilla, Joaquin Quiñ...