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» A Boosting Algorithm for Regression
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CVPR
2010
IEEE
14 years 11 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
SDM
2008
SIAM
119views Data Mining» more  SDM 2008»
15 years 21 days 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
AIA
2007
15 years 22 days ago
Improving the aggregating algorithm for regression
Kernel Ridge Regression (KRR) and the recently developed Kernel Aggregating Algorithm for Regression (KAAR) are regression methods based on Least Squares. KAAR has theoretical adv...
Steven Busuttil, Yuri Kalnishkan, Alexander Gammer...
FOCM
2007
76views more  FOCM 2007»
14 years 11 months ago
Risk Bounds for Random Regression Graphs
We consider the regression problem and describe an algorithm approximating the regression function by estimators piecewise constant on the elements of an adaptive partition. The pa...
Andrea Caponnetto, Steve Smale
KES
2006
Springer
14 years 11 months ago
Sensor Network Localization Using Least Squares Kernel Regression
Abstract. This paper considers the sensor network localization problem using signal strength. Unlike range-based methods signal strength information is stored in a kernel matrix. L...
Anthony Kuh, Chaopin Zhu, Danilo P. Mandic