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NIPS
2008
14 years 11 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
FUZZIEEE
2007
IEEE
15 years 1 months ago
Evolving Single- and Multi-Model Fuzzy Classifiers with FLEXFIS-Class
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
Edwin Lughofer, Plamen P. Angelov, Xiaowei Zhou
JCP
2006
118views more  JCP 2006»
14 years 9 months ago
Learning a Classification-based Glioma Growth Model Using MRI Data
Gliomas are malignant brain tumors that grow by invading adjacent tissue. We propose and evaluate a 3D classification-based growth model, CDM, that predicts how a glioma will grow ...
Marianne Morris, Russell Greiner, Jörg Sander...
BMCBI
2010
105views more  BMCBI 2010»
14 years 9 months ago
Comparison of PGH2 binding site in prostaglandin synthases
Background: Prostaglandin H2 (PGH2) is a common precursor for the synthesis of five different Prostanoids via specific Prostanoid Synthases. The binding of this substrate with the...
Padmapriya Paragi-Vedanthi, Mukesh Doble
97
Voted
EVOW
2003
Springer
15 years 2 months ago
Comparison of AdaBoost and Genetic Programming for Combining Neural Networks for Drug Discovery
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...