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» VIF Regression: A Fast Regression Algorithm for Large Data
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WWW
2011
ACM
13 years 2 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
KDD
2004
ACM
131views Data Mining» more  KDD 2004»
14 years 8 months ago
Fast nonlinear regression via eigenimages applied to galactic morphology
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...
CSDA
2007
152views more  CSDA 2007»
13 years 7 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch
SDM
2008
SIAM
119views Data Mining» more  SDM 2008»
13 years 9 months ago
An Efficient Local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks
This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm is designed for distributed inferencing, data compact...
Kanishka Bhaduri, Hillol Kargupta
AUSAI
2008
Springer
13 years 9 months ago
Additive Regression Applied to a Large-Scale Collaborative Filtering Problem
Abstract. The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms...
Eibe Frank, Mark Hall