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IJON
2008
156views more  IJON 2008»
13 years 8 months ago
Structural identifiability of generalized constraint neural network models for nonlinear regression
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
Shuang-Hong Yang, Bao-Gang Hu, Paul-Henry Courn&eg...
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 6 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
ESANN
2007
13 years 10 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley
PRL
2008
101views more  PRL 2008»
13 years 7 months ago
Illumination-robust face recognition using ridge regressive bilinear models
The performance of face recognition is greatly affected by illumination changes because intra-person variation of the captured images under different lighting conditions can be mu...
Dongsoo Shin, Hyung-Soo Lee, Daijin Kim
MA
2010
Springer
172views Communications» more  MA 2010»
13 years 7 months ago
On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Vivekananda Roy, James P. Hobert