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ESEM
2008
ACM
13 years 10 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
ICSM
1993
IEEE
14 years 20 days ago
Incremental Regression Testing
The purpose of regression testing is to ensure that bug xes and new functionality introduced in a new version of a software do not adversely a ect the correct functionality inheri...
Hiralal Agrawal, Joseph Robert Horgan, Edward W. K...
NIPS
2008
13 years 10 months ago
Privacy-preserving logistic regression
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Kamalika Chaudhuri, Claire Monteleoni
CVPR
2010
IEEE
13 years 8 months ago
Robust RVM regression using sparse outlier model
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...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
SOCO
2008
Springer
13 years 8 months ago
Fuzzy linear regression model based on fuzzy scalar product
The new concept and method of imposing imprecise (fuzzy) input and output data upon the conventional linear regression model is proposed in this paper. We introduce the fuzzy scala...
Hsien-Chung Wu