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» Feature Subset Selection Using a Genetic Algorithm
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TSMC
2002
110views more  TSMC 2002»
15 years 2 months ago
Complexity reduction for "large image" processing
We present a method for sampling feature vectors in large (e.g., 2000 5000 16 bit) images that finds subsets of pixel locations which represent "regions" in the image. Sa...
Nikhil R. Pal, James C. Bezdek
WWW
2009
ACM
16 years 3 months ago
Bid optimization for broad match ad auctions
Ad auctions in sponsored search support"broad match"that allows an advertiser to target a large number of queries while bidding only on a limited number. While giving mo...
Eyal Even-Dar, Vahab S. Mirrokni, S. Muthukrishnan...
CVPR
2006
IEEE
15 years 9 months ago
Real Time Localization and 3D Reconstruction
In this paper we describe a method that estimates the motion of a calibrated camera (settled on an experimental vehicle) and the tridimensional geometry of the environment. The on...
E. Mouragnon, Fabien Dekeyser, Patrick Sayd, Maxim...
SYNASC
2005
IEEE
77views Algorithms» more  SYNASC 2005»
15 years 8 months ago
On P Systems with Bounded Parallelism
— A framework that describes the evolution of P systems with bounded parallelism is defined by introducing basic formal features that can be then integrated into a structural op...
Francesco Bernardini, Francisco José Romero...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 4 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...