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TNN
2008
119views more  TNN 2008»
15 years 6 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
TNN
2008
114views more  TNN 2008»
15 years 6 months ago
Relevance-Based Feature Extraction for Hyperspectral Images
Abstract--Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific re...
Michael J. Mendenhall, Erzsébet Meré...
JFP
2002
96views more  JFP 2002»
15 years 6 months ago
Secrets of the Glasgow Haskell Compiler inliner
Higher-order languages, such as Haskell, encourage the proto build abstractions by composing functions. A good compiler must inline many of these calls to recover an e ciently exe...
Simon L. Peyton Jones, Simon Marlow
MCS
2002
Springer
15 years 6 months ago
Boosting and Classification of Electronic Nose Data
Abstract. Boosting methods are known to improve generalization performances of learning algorithms reducing both bias and variance or enlarging the margin of the resulting multi-cl...
Francesco Masulli, Matteo Pardo, Giorgio Sbervegli...
AUSAI
2010
Springer
15 years 5 months ago
Heuristic Planning with SAT: Beyond Uninformed Depth-First Search
Abstract. Planning-specific heuristics for SAT have recently been shown to produce planners that match best earlier ones that use other search methods, including the until now dom...
Jussi Rintanen