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» Computational complexity of stochastic programming problems
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JPDC
2006
175views more  JPDC 2006»
13 years 11 months ago
Stochastic modeling and analysis of hybrid mobility in reconfigurable distributed virtual machines
Virtualization provides a vehicle to manage the available resources and enhance their utilization in network computing. System dynamics requires virtual machines be distributed an...
Song Fu, Cheng-Zhong Xu
STACS
2005
Springer
14 years 4 months ago
Kolmogorov-Loveland Randomness and Stochasticity
An infinite binary sequence X is Kolmogorov-Loveland (or KL) random if there is no computable non-monotonic betting strategy that succeeds on X in the sense of having an unbounde...
Wolfgang Merkle, Joseph S. Miller, André Ni...
TNN
2008
138views more  TNN 2008»
13 years 11 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany
EPEW
2006
Springer
14 years 2 months ago
Model Checking for a Class of Performance Properties of Fluid Stochastic Models
Abstract. Recently, there is an explosive development of fluid approaches to computer and distributed systems. These approaches are inherently stochastic and generate continuous st...
Manuela L. Bujorianu, Marius C. Bujorianu
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 5 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay