1183 search results - page 45 / 237 » Learning Process Models with Missing Data |
102
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ECCV
2010
Springer
15 years 6 months ago
2010
Springer
Abstract. We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at appl...
112
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ESSMAC
2003
Springer
15 years 6 months ago
2003
Springer
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
112
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ICCV
2005
IEEE
16 years 3 months ago
2005
IEEE
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
103
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
ICANN
2001
Springer
15 years 5 months ago
2001
Springer
We distinguish between two main types of model: predictive and explanatory. It is argued (in the absence of models that predict on unseen data) that in order for a model to increas...