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» Genetic algorithms using low-discrepancy sequences
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110
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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 9 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
EVOW
2010
Springer
15 years 6 months ago
Towards Automated Learning of Object Detectors
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
Marc Ebner
BMCBI
2007
156views more  BMCBI 2007»
15 years 3 months ago
Predictive modeling of plant messenger RNA polyadenylation sites
Background: One of the essential processing events during pre-mRNA maturation is the posttranscriptional addition of a polyadenine [poly(A)] tail. The 3'-end poly(A) track pr...
Guoli Ji, Jianti Zheng, Yingjia Shen, Xiaohui Wu, ...
144
Voted
BMCBI
2007
180views more  BMCBI 2007»
15 years 3 months ago
Using expression arrays for copy number detection: an example from E. coli
Background: The sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible...
Dmitriy Skvortsov, Diana Abdueva, Michael E. Stitz...
123
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GECCO
1999
Springer
15 years 7 months ago
An Immune System Approach to Scheduling in Changing Environments
This paper describes the application of an arti cial immune system, AIS, model to a scheduling application, in which sudden changes in the scheduling environment require the rap...
Emma Hart, Peter Ross