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» Optimizing Feature Sets for Structured Data
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ISNN
2007
Springer
14 years 1 months ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
14 years 1 months ago
A NSGA-II, web-enabled, parallel optimization framework for NLP and MINLP
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time con...
David J. Powell, Joel K. Hollingsworth
BMCBI
2010
158views more  BMCBI 2010»
13 years 7 months ago
A Bayesian network approach to feature selection in mass spectrometry data
Background: Time-of-flight mass spectrometry (TOF-MS) has the potential to provide non-invasive, high-throughput screening for cancers and other serious diseases via detection of ...
Karl W. Kuschner, Dariya I. Malyarenko, William E....
ICANN
2009
Springer
14 years 2 months ago
Learning Features by Contrasting Natural Images with Noise
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...
Michael Gutmann, Aapo Hyvärinen
SPAA
2010
ACM
13 years 7 months ago
A universal construction for wait-free transaction friendly data structures
Given the sequential implementation of any data structure, we show how to obtain an efficient, wait-free implementation of that data structure shared by any fixed number of proces...
Phong Chuong, Faith Ellen, Vijaya Ramachandran