Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
In this paper, an efficient simulation environment that utilizes compiler techniques to speed up simulation is presented. The method is based on the utilization of flexible, proce...
The paper evaluates the eectiveness of learning for speeding up the solution of constraint satisfaction problems. It extends previous work (Dechter 1990) by introducing a new and ...
Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a singl...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...
This paper uses a configuration space ( -space) based method to compute interference-free configuration for stacking polyhedral sheet metal parts. This work forms the interference ...
Venkateswara R. Ayyadevara, David A. Bourne, Kenji...