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» Approximate Learning of Dynamic Models
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INFORMS
1998
100views more  INFORMS 1998»
13 years 10 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...
IHI
2010
197views Healthcare» more  IHI 2010»
13 years 5 months ago
Beyond safe harbor: automatic discovery of health information de-identification policy alternatives
Regulations in various countries permit the reuse of health information without patient authorization provided the data is "de-identified". In the United States, for ins...
Kathleen Benitez, Grigorios Loukides, Bradley Mali...
FGR
2011
IEEE
227views Biometrics» more  FGR 2011»
13 years 2 months ago
Warp that smile on your face: Optimal and smooth deformations for face recognition
— In this work, we present novel warping algorithms for full 2D pixel-grid deformations for face recognition. Due to high variation in face appearance, face recognition is consid...
Tobias Gass, Leonid Pishchulin, Philippe Dreuw, He...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 11 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
SIGMOD
2008
ACM
138views Database» more  SIGMOD 2008»
14 years 11 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
Rainer Gemulla, Wolfgang Lehner