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» A Boosting Algorithm for Regression
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JMLR
2010
110views more  JMLR 2010»
14 years 11 months ago
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
A new approach to regression regularization called the Pairwise Elastic Net is proposed. Like the Elastic Net, it simultaneously performs automatic variable selection and continuo...
Alexander Lorbert, David Eis, Victoria Kostina, Da...
ICASSP
2011
IEEE
14 years 7 months ago
Sparse variable reduced rank regression via Stiefel optimization
Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...
Magnus O. Ulfarsson, Victor Solo
IJCNN
2006
IEEE
15 years 10 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
ICMCS
2005
IEEE
78views Multimedia» more  ICMCS 2005»
15 years 9 months ago
Partial Linear Regression for Audio-Driven Talking Head Application
Virtual avatars in many applications are constructed manually or by a single speech-driven model which needs a lot of training data and long training time. It’s an essential pro...
Chao-Kuei Hsieh, Yung-Chang Chen
SCALESPACE
2005
Springer
15 years 9 months ago
Relations Between Higher Order TV Regularization and Support Vector Regression
We study the connection between higher order total variation (TV) regularization and support vector regression (SVR) with spline kernels in a one-dimensional discrete setting. We p...
Gabriele Steidl, Stephan Didas, Julia Neumann