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IPMI
2011
Springer
8 years 5 months ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
INFORMATICALT
2011
112views more  INFORMATICALT 2011»
8 years 9 months ago
The Minimum Density Power Divergence Approach in Building Robust Regression Models
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
Alessandra Durio, Ennio Davide Isaia
NPL
2002
168views more  NPL 2002»
9 years 1 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot
CSDA
2010
172views more  CSDA 2010»
9 years 2 months ago
Testing for two components in a switching regression model
We consider switching regression models with independent or Markov-dependent regime. Based on the modified likelihood ratio test (LRT) statistic by Chen, Chen and Kalbfleisch (200...
Jörn Dannemann, Hajo Holzmann
CSDA
2010
175views more  CSDA 2010»
9 years 2 months ago
Testing, monitoring, and dating structural changes in exchange rate regimes
Linear regression models for de facto exchange rate regime classification are complemented by inferential techniques for evaluating the stability of the regimes. To simultaneously...
Achim Zeileis, Ajay Shah, Ila Patnaik
CGF
2010
161views more  CGF 2010»
9 years 2 months ago
HyperMoVal: Interactive Visual Validation of Regression Models for Real-Time Simulation
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
Harald Piringer, Wolfgang Berger, J. Krasser
SDM
2004
SIAM
144views Data Mining» more  SDM 2004»
9 years 3 months ago
RBA: An Integrated Framework for Regression based on Association Rules
This paper explores a novel framework for building regression models using association rules. The model consists of an ordered set of IF-THEN rules, where the rule consequent is t...
Aysel Ozgur, Pang-Ning Tan, Vipin Kumar
NIPS
2001
9 years 3 months ago
Infinite Mixtures of Gaussian Process Experts
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
Carl Edward Rasmussen, Zoubin Ghahramani
ESANN
2006
9 years 3 months ago
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
Aloísio Carlos de Pina, Gerson Zaverucha
ESEM
2008
ACM
9 years 4 months ago
Fit data selection for software effort estimation models
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...
Koji Toda, Akito Monden, Ken-ichi Matsumoto
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