1183 search results - page 19 / 237 » Learning Process Models with Missing Data |
NIPS
2004
15 years 2 months ago
2004
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
106
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TSMC
2011
14 years 8 months ago
2011
— Most state-based approaches to fault diagnosis of discrete-event systems require a complete and accurate model of the system to be diagnosed. In this paper, we address the prob...
106
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PAMI
2008
15 years 1 months ago
2008
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
117
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PKDD
2010
Springer
14 years 11 months ago
2010
Springer
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
125
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...