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» Margin based feature selection - theory and algorithms
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IJCNN
2000
IEEE
14 years 1 days ago
Supervised Scaled Regression Clustering: An Alternative to Neural Networks
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...
DAC
2009
ACM
14 years 10 days ago
Vicis: a reliable network for unreliable silicon
Process scaling has given designers billions of transistors to work with. As feature sizes near the atomic scale, extensive variation and wearout inevitably make margining unecono...
David Fick, Andrew DeOrio, Jin Hu, Valeria Bertacc...
ATAL
2006
Springer
13 years 11 months ago
Information-theoretic approaches to branching in search
Deciding what to branch on at each node is a key element of search algorithms. We present four families of methods for selecting what question to branch on. They are all informati...
Andrew Gilpin, Tuomas Sandholm
KES
2007
Springer
13 years 7 months ago
An Application of Machine Learning Methods to PM10 Level Medium-Term Prediction
The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants...
Giovanni Raimondo, Alfonso Montuori, Walter Moniac...
BMCBI
2010
146views more  BMCBI 2010»
13 years 7 months ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han