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» A neural network approach to ordinal regression
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IJCNN
2008
IEEE
15 years 3 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
NN
2010
Springer
189views Neural Networks» more  NN 2010»
14 years 4 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
BMCBI
2007
136views more  BMCBI 2007»
14 years 9 months ago
Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
Xiaoyu Chen, Mathieu Blanchette
ECAI
2004
Springer
15 years 2 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
GECCO
2004
Springer
169views Optimization» more  GECCO 2004»
15 years 2 months ago
Genetic Programming Neural Networks as a Bioinformatics Tool for Human Genetics
The identification of genes that influence the risk of common, complex diseases primarily through interactions with other genes and environmental factors remains a statistical and ...
Marylyn D. Ritchie, Christopher S. Coffey, Jason H...