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» A flexible approach to Bayesian multiple curve fitting
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NIPS
2004
13 years 6 months ago
Following Curved Regularized Optimization Solution Paths
Regularization plays a central role in the analysis of modern data, where non-regularized fitting is likely to lead to over-fitted models, useless for both prediction and interpre...
Saharon Rosset
PRL
2008
132views more  PRL 2008»
13 years 5 months ago
Confidence based multiple classifier fusion in speaker verification
A novel framework based on Bayes-based confidence measure for Multiple Classifier System fusion is proposed. Compared with ordinary Bayesian fusion, the presented approach leads t...
Fernando Huenupán, Néstor Becerra Yo...
ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
13 years 3 months ago
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
BMCBI
2006
187views more  BMCBI 2006»
13 years 5 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
WWW
2003
ACM
14 years 6 months ago
Predicting the Upper Bound of Web Traffic Volume Using a Multiple Time Scale Approach
This paper presents a prediction algorithm for estimating the upper bound of future Web traffic volume. Unlike traditional traffic predictions that are performed at a single time ...
Weibin Zhao, Henning Schulzrinne