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GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
15 years 9 months ago
Investigating whether hyperNEAT produces modular neural networks
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 9 months ago
Evolving the placement and density of neurons in the hyperneat substrate
The Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT) approach demonstrated that the pattern of weights across the connectivity of an artificial neural network ...
Sebastian Risi, Joel Lehman, Kenneth O. Stanley
INFOCOM
2000
IEEE
15 years 8 months ago
Energy Conserving Routing in Wireless Ad-hoc Networks
— An ad-hoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and need...
Jae-Hwan Chang, Leandros Tassiulas
ASPLOS
2000
ACM
15 years 8 months ago
Software Profiling for Hot Path Prediction: Less is More
Recently, there has been a growing interest in exploiting profile information in adaptive systems such as just-in-time compilers, dynamic optimizers and, binary translators. In th...
Evelyn Duesterwald, Vasanth Bala
CIKM
1999
Springer
15 years 8 months ago
Requirement-Based Data Cube Schema Design
On-line analytical processing (OLAP) requires e cient processing of complex decision support queries over very large databases. It is well accepted that pre-computed data cubes ca...
David Wai-Lok Cheung, Bo Zhou, Ben Kao, Hongjun Lu...
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