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APIN
1999
107views more  APIN 1999»
13 years 10 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
PODS
2007
ACM
196views Database» more  PODS 2007»
14 years 11 months ago
On the complexity of managing probabilistic XML data
In [3], we introduced a framework for querying and updating probabilistic information over unordered labeled trees, the probabilistic tree model. The data model is based on trees ...
Pierre Senellart, Serge Abiteboul
WEBDB
2007
Springer
126views Database» more  WEBDB 2007»
14 years 5 months ago
Towards a Content-Provider-Friendly Web Page Crawler
Search engine quality is impacted by two factors: the quality of the ranking/matching algorithm used and the freshness of the search engine’s index, which maintains a “snapsho...
Jie Xu, Qinglan Li, Huiming Qu, Alexandros Labrini...
CVPR
2010
IEEE
13 years 11 months ago
A probabilistic framework for joint segmentation and tracking
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
Chad Aeschliman, Johnny Park, Avinash C. Kak
ALT
1997
Springer
14 years 2 months ago
Learning One-Variable Pattern Languages Very Efficiently on Average, in Parallel, and by Asking Queries
A pattern is a string of constant and variable symbols. The language generated by a pattern is the set of all strings of constant symbols which can be obtained from by substituti...
Thomas Erlebach, Peter Rossmanith, Hans Stadtherr,...