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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...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 10 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
16 years 4 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
ISSAC
2007
Springer
142views Mathematics» more  ISSAC 2007»
15 years 10 months ago
Fast arithmetic for triangular sets: from theory to practice
We study arithmetic operations for triangular families of polynomials, concentrating on multiplication in dimension zero. By a suitable extension of fast univariate Euclidean divi...
Xin Li, Marc Moreno Maza, Éric Schost
COMPGEOM
2005
ACM
15 years 5 months ago
Inclusion-exclusion formulas from independent complexes
Using inclusion-exclusion, we can write the indicator function of a union of finitely many balls as an alternating sum of indicator functions of common intersections of balls. We...
Dominique Attali, Herbert Edelsbrunner