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JMLR
2010
202views more  JMLR 2010»
14 years 10 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
DSOM
1999
Springer
15 years 7 months ago
Derivation of Backup Service Management Applications from Service and System Models
The backup of large data sets is preferably performed automatically outside of regular working hours. In highly structured computer networks, however, faults and exceptions may rel...
Ingo Lück, Marcus Schönbach, Arnulf Mest...
CORR
2011
Springer
195views Education» more  CORR 2011»
14 years 10 months ago
Abstract Processes of Place/Transition Systems
Processes of Place/Transition Systems6 Rob van Glabbeeka,b , Ursula Goltzc , Jens-Wolfhard Schickec aNICTA, Sydney, Australia bSchool of Computer Science and Engineering, Universit...
Rob J. van Glabbeek, Ursula Goltz, Jens-Wolfhard S...
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IEEEPACT
2006
IEEE
15 years 9 months ago
Compiling for stream processing
This paper describes a compiler for stream programs that efficiently schedules computational kernels and stream memory operations, and allocates on-chip storage. Our compiler uses...
Abhishek Das, William J. Dally, Peter R. Mattson
GECCO
2005
Springer
384views Optimization» more  GECCO 2005»
15 years 8 months ago
A case study of process facility optimization using discrete event simulation and genetic algorithm
Optimization problems such as resource allocation, job-shop scheduling, equipment utilization and process scheduling occur in a broad range of processing industries. This paper pr...
Keshav P. Dahal, Stuart Galloway, Graeme M. Burt, ...