A Two-Layer Mixture Model of Gaussian Process Functional Regressions and Its MCMC EM Algorithm.
IEEE Transactions on Neural Networks and Learning Systems（2018）
摘要
The mixture of Gaussian processes (GPs) is capable of learning any general stochastic process based on a given set of (sample) curves for the regression and prediction problems. However, it is ineffective for curve clustering and prediction, when the sample curves are derived from different stochastic processes as independent sources linearly mixed together. In this paper, we propose a two-layer m...
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关键词
Clustering algorithms,Prediction algorithms,Approximation algorithms,Mixture models,Stochastic processes,Monte Carlo methods,Data models
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