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| Robust Regression Using Sparse Learning
 
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===Robust Regression Using Sparse Learning===
 
Speaker: [http://www.umiacs.umd.edu/~kmitra/ Kaushik Mitra] -- Date: July 21, 2011
 
Speaker: [http://www.umiacs.umd.edu/~kmitra/ Kaushik Mitra] -- Date: July 21, 2011
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Robust regression is a combinatorial optimization problem. Hence, algorithms such as RANSAC and least median squares (LMedS), which are successful in solving low-dimensional problems, can not be used for solving high-dimensional problems. We show that under certain conditions the robust linear regression problem can be solved accurately using polynomial-time algorithms such as a modified version of basis pursuit and a sparse Bayesian algorithm. We then extend our robust formulation to the case of kernel regression, specifically to propose a robust version for relevance vector machine (RVM) regression.
     
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