3694 search results - page 126 / 739 » Stochastic complexity in learning |
TFS
2011
13 years 5 months ago
2011
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
JMLR
2010
13 years 5 months ago
2010
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
ECRTS
2003
IEEE
14 years 3 months ago
2003
IEEE
When time-triggered (TT) systems are to be deployed for large embedded real-time (RT) control systems in cars and airplanes, one way to overcome bandwidth limitations and achieve ...
CCE
2008
13 years 10 months ago
2008
Deterministic optimization approaches have been well developed and widely used in the process industry to accomplish off-line and on-line process optimization. The challenging tas...
AAAI
2011
12 years 10 months ago
2011
Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (m...