922 search results - page 82 / 185 » Learning Gaussian Process Models from Uncertain Data |
139
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NIPS
1998
15 years 3 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
126
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ICCS
2004
Springer
15 years 7 months ago
2004
Springer
Air pollution models usually start from the computation of the velocity field of a fluid. In this paper, we present a model for computing that field based on the contribution of...
112
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COLT
2004
Springer
15 years 8 months ago
2004
Springer
Abstract. The Gram matrix plays a central role in many kernel methods. Knowledge about the distribution of eigenvalues of the Gram matrix is useful for developing appropriate model...
137
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ER
1999
Springer
15 years 6 months ago
1999
Springer
Abstract. The process industries (chemicals, food, oil, ...) are characterized by - continuous or batch -- processes of material transformation. The design of such processes, and t...
120
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PAMI
2006
15 years 2 months ago
2006
This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar a...