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» Introduction to Randomized Algorithms
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CATA
2009
15 years 4 months ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
EOR
2010
116views more  EOR 2010»
15 years 3 months ago
Speeding up continuous GRASP
Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hi...
Michael J. Hirsch, Panos M. Pardalos, Mauricio G. ...
CORR
2007
Springer
183views Education» more  CORR 2007»
15 years 3 months ago
Compressed Sensing and Redundant Dictionaries
This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, whic...
Holger Rauhut, Karin Schnass, Pierre Vandergheynst
ISSTA
2012
ACM
13 years 6 months ago
Swarm testing
Swarm testing is a novel and inexpensive way to improve the diversity of test cases generated during random testing. Increased diversity leads to improved coverage and fault detec...
Alex Groce, Chaoqiang Zhang, Eric Eide, Yang Chen,...
VDB
1998
117views Database» more  VDB 1998»
15 years 5 months ago
Textural Features and Relevance Feedback for Image Retrieval
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...