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UAI
1996
15 years 8 months ago
An evaluation of structural parameters for probabilistic reasoning: Results on benchmark circuits
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithmse.g., clustering, conditioning ar...
Yousri El Fattah, Rina Dechter
IJCAI
1989
15 years 8 months ago
Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge
This paper highlights a phenomenon that causes deductively learned knowledge to be harmful when used for problem solving. The problem occurs when deductive problem solvers encount...
Shaul Markovitch, Paul D. Scott
CIBCB
2009
IEEE
15 years 8 months ago
Application of machine learning approaches on quantitative structure activity relationships
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
Mariusz Butkiewicz, Ralf Mueller, Danilo Selic, Er...
CN
2006
79views more  CN 2006»
15 years 6 months ago
Explicit rate multicast congestion control
In this article, we propose a new single-rate end-to-end multicast congestion control scheme called Explicit Rate Multicast Congestion Control (ERMCC) based on a new metric, TRAC ...
Jiang Li, Murat Yuksel, Shivkumar Kalyanaraman
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 6 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek