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ECML
2006
Springer
15 years 7 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
139
Voted
SPIESR
2001
133views Database» more  SPIESR 2001»
15 years 4 months ago
Shot detection combining Bayesian and structural information
There are a number of shots in a video, each of which has boundary types, such as cut, fade, dissolve and wipe. Many previous approaches can find the cut boundary without difficul...
Seung-Hoon Han, In-So Kweon
131
Voted
UAI
1993
15 years 4 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
140
Voted
UAI
1996
15 years 4 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
152
Voted
ECAI
2010
Springer
15 years 4 months ago
Using Bayesian Networks in an Industrial Setting: Making Printing Systems Adaptive
Abstract. Control engineering is a field of major industrial importance as it offers principles for engineering controllable physical devices, such as cell phones, television sets,...
Arjen Hommersom, Peter J. F. Lucas