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» Computing LTS Regression for Large Data Sets
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DATAMINE
2006
127views more  DATAMINE 2006»
13 years 5 months ago
Computing LTS Regression for Large Data Sets
Least trimmed squares (LTS) regression is based on the subset of h cases (out of n) whose least squares t possesses the smallest sum of squared residuals. The coverage h may be se...
Peter Rousseeuw, Katrien van Driessen
ICML
2005
IEEE
14 years 5 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
ESSMAC
2003
Springer
13 years 10 months ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...
KDD
2004
ACM
285views Data Mining» more  KDD 2004»
13 years 10 months ago
Effective localized regression for damage detection in large complex mechanical structures
In this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. Every mechanical structure is defi...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
CSR
2007
Springer
13 years 11 months ago
Estimation of the Click Volume by Large Scale Regression Analysis
Abstract. How could one estimate the total number of clicks a new advertisement could potentially receive in the current market? This question, called the click volume estimation p...
Yury Lifshits, Dirk Nowotka