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» Adaptive Sparse Grid Classification Using Grid Environments
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NECO
2008
114views more  NECO 2008»
13 years 7 months ago
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
Cornelius Weber, Jochen Triesch
IPPS
2005
IEEE
14 years 1 months ago
Using Message-Driven Objects to Mask Latency in Grid Computing Applications
One of the attractive features of Grid computing is that resources in geographically distant places can be mobilized to meet computational needs as they arise. A particularly chal...
Gregory A. Koenig, Laxmikant V. Kalé
DEXAW
2004
IEEE
123views Database» more  DEXAW 2004»
13 years 11 months ago
Self-Adaptive and Self-Optimising Resource Monitoring for Dynamic Grid Environments
As the number of resources on the Grid tends to be very dynamic and potentially large, it becomes increasingly important to discover and monitor them efficiently. This paper conce...
Helene N. Lim Choi Keung, Justin R. D. Dyson, Step...
IEEEHPCS
2010
13 years 5 months ago
Using replication and checkpointing for reliable task management in computational Grids
In grid computing systems, providing fault-tolerance is required for both scientific computation and file-sharing to increase their reliability. In previous works, several mechani...
Sangho Yi, Derrick Kondo, Bongjae Kim, Geunyoung P...
CCGRID
2007
IEEE
14 years 2 months ago
Adaptive Performance Modeling on Hierarchical Grid Computing Environments
In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, d...
Wahid Nasri, Luiz Angelo Steffenel, Denis Trystram