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» Direct Zero-Norm Optimization for Feature Selection
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IEEEPACT
2008
IEEE
15 years 8 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
109
Voted
CEC
2010
IEEE
15 years 2 months ago
Classifier-assisted constrained evolutionary optimization for automated geometry selection of orthodontic retraction spring
In orthodontics, retraction springs made of metallic wires are often used to move a tooth with respect to another by the virtue of the spring back effect. Specially selected form o...
Dudy Lim, Yew-Soon Ong, Rachman Setiawan, Muhammad...
PAA
2010
15 years 5 days ago
Exploiting visual and text features for direct marketing learning in time and space constrained domains
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audiences. Companies systematically dispatch the offers under consid...
Sebastiano Battiato, Giovanni Maria Farinella, Gio...
ICIP
2003
IEEE
16 years 3 months ago
Optimal Gabor kernel location selection for face recognition
In local feature?based face recognition systems, the topographical locations of feature extractors directly affect the discriminative power of a recognizer. Better recognition acc...
Berk Gökberk, Ethem Alpaydin, Lale Akarun, M....
113
Voted
NAACL
2004
15 years 3 months ago
A Smorgasbord of Features for Statistical Machine Translation
We describe a methodology for rapid experimentation in statistical machine translation which we use to add a large number of features to a baseline system exploiting features from...
Franz Josef Och, Daniel Gildea, Sanjeev Khudanpur,...