11151 search results - page 383 / 2231 » On the Complexity of Model Expansion |
226
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CSDA
2007
15 years 7 months ago
2007
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
211
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SIGMOD
2010
ACM
15 years 2 months ago
2010
ACM
Probabilistic processes appear naturally in various contexts, with applications to Business Processes, XML data management and more. Many models for specifying and querying such p...
216
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CVPR
1997
IEEE
16 years 9 months ago
1997
IEEE
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
224
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CVPR
1999
IEEE
16 years 9 months ago
1999
IEEE
A spatio-temporal representation for complex optical flow events is developed that generalizes traditional parameterized motion models (e.g. affine). These generative spatio-tempo...
191
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KDD
2006
ACM
16 years 8 months ago
2006
ACM
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classif...