243 search results - page 3 / 49 » Non-linear regression models for Approximate Bayesian Comput... |
NIPS
2008
13 years 7 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
IJCAI
2007
13 years 7 months ago
2007
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
CVPR
2010
IEEE
13 years 6 months ago
2010
IEEE
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...