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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 10 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
139
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
15 years 5 months ago
Evolution of discrete gene regulatory models
Gene regulatory networks (GRNs) are complex control systems that govern the interaction of genes, which ultimately control cellular processes at the protein level. GRNs can be ted...
Afshin Esmaeili, Christian Jacob
SIGCOMM
2010
ACM
15 years 4 months ago
Helios: a hybrid electrical/optical switch architecture for modular data centers
The basic building block of ever larger data centers has shifted from a rack to a modular container with hundreds or even thousands of servers. Delivering scalable bandwidth among...
Nathan Farrington, George Porter, Sivasankar Radha...
NCA
2006
IEEE
15 years 4 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
PERCOM
2005
ACM
16 years 4 months ago
Determination of Time and Order for Event-Based Middleware in Mobile Peer-to-Peer Environments
An event correlation is becoming an important service in event-based middleware allowing subscribers in publish/subscribe paradigm to consume patterns of events (composite events)...
Eiko Yoneki, Jean Bacon