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» Stochastic complexity in learning
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DSN
2000
IEEE
15 years 10 months ago
DEEM: A Tool for the Dependability Modeling and Evaluation of Multiple Phased Systems
Multiple-Phased Systems, whose operational life can be partitioned in a set of disjoint periods, called “phases”, include several classes of systems such as Phased Mission Sys...
Andrea Bondavalli, Ivan Mura, Silvano Chiaradonna,...
KR
1989
Springer
15 years 10 months ago
Situated Control Rules
In this work we extend the work of Dean, Kaelbling, Kirman and Nicholson on planning under time constraints in stochastic domains to handle more complicated scheduling problems. I...
Mark Drummond
ADVIS
2004
Springer
15 years 9 months ago
On Families of New Adaptive Compression Algorithms Suitable for Time-Varying Source Data
In this paper, we introduce a new approach to adaptive coding which utilizes Stochastic Learning-based Weak Estimation (SLWE) techniques to adaptively update the probabilities of t...
Luís G. Rueda, B. John Oommen
WSC
2007
15 years 8 months ago
Path-sampling for state-dependent importance sampling
State-dependent importance sampling (SDIS) has proved to be particularly useful in simulation (specially in rare event analysis of stochastic systems). One approach for designing ...
Jose H. Blanchet, Jingchen Liu
WSC
2008
15 years 8 months ago
Approximate dynamic programming: Lessons from the field
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
Warren B. Powell