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ICANN
2009
Springer
15 years 6 months ago
Evolving Memory Cell Structures for Sequence Learning
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
Justin Bayer, Daan Wierstra, Julian Togelius, J&uu...
HPCC
2007
Springer
15 years 6 months ago
CDACAN: A Scalable Structured P2P Network Based on Continuous Discrete Approach and CAN
Abstract. CAN is a famous structured peer-to-peer network based on ddimensional torus topology with constant degree and logarithmical diameter, but suffers from poor scalability wh...
Lingwei Li, Qunwei Xue, Deke Guo
GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
15 years 5 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
SIAMJO
2010
121views more  SIAMJO 2010»
14 years 10 months ago
Optimization Strategies for the Vulnerability Analysis of the Electric Power Grid
Identifying small groups of lines, whose removal would cause a severe blackout, is critical for the secure operation of the electric power grid. We show how power grid vulnerabilit...
Ali Pinar, Juan Meza, Vaibhav Donde, Bernard C. Le...
ISCA
2010
IEEE
204views Hardware» more  ISCA 2010»
15 years 4 months ago
Energy proportional datacenter networks
Numerous studies have shown that datacenter computers rarely operate at full utilization, leading to a number of proposals for creating servers that are energy proportional with r...
Dennis Abts, Michael R. Marty, Philip M. Wells, Pe...