219 search results - page 29 / 44 » Learning the Dimensionality of Hidden Variables |
ICML
2008
IEEE
16 years 15 days ago
2008
IEEE
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
PAMI
2008
14 years 11 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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KDD
2008
ACM
16 years 3 days ago
2008
ACM
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
116
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UAI
2000
15 years 1 months ago
2000
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
107
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NIPS
2007
15 years 1 months ago
2007
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...