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SIGMOD
2010
ACM
231views Database» more  SIGMOD 2010»
15 years 2 months ago
Automatically incorporating new sources in keyword search-based data integration
Scientific data offers some of the most interesting challenges in data integration today. Scientific fields evolve rapidly and accumulate masses of observational and experiment...
Partha Pratim Talukdar, Zachary G. Ives, Fernando ...
GECCO
2010
Springer
155views Optimization» more  GECCO 2010»
15 years 2 months ago
Negative selection algorithms without generating detectors
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Maciej Liskiewicz, Johannes Textor
GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
15 years 2 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...
MM
2009
ACM
187views Multimedia» more  MM 2009»
15 years 2 months ago
Convex experimental design using manifold structure for image retrieval
Content Based Image Retrieval (CBIR) has become one of the most active research areas in computer science. Relevance feedback is often used in CBIR systems to bridge the semantic ...
Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng ...
GECCO
2009
Springer
15 years 2 months ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock