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JISE
2008
77views more  JISE 2008»
13 years 9 months ago
Formalized Entity Extraction Methodology for Changeable Business Requirements
business requirement in the real world cannot be abstracted correctly into an entity-relationship schema. Once core entities are discovered, we can obtain an Entity-Relationship Di...
Namgyu Kim, Sangwon Lee, Songchun Moon
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 9 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
CIDM
2009
IEEE
14 years 4 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
FGR
2004
IEEE
132views Biometrics» more  FGR 2004»
14 years 1 months ago
Expand Training Set for Face Detection by GA Re-sampling
Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. All of the statistical methods suffer from this ...
Jie Chen, Xilin Chen, Wen Gao
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 29 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa