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» Active Learning with Model Selection in Linear Regression
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TCS
2010
13 years 7 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
DIS
2007
Springer
14 years 2 months ago
Discovering Communicable Models from Earth Science Data
Abstract. This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of mac...
Mark Schwabacher, Pat Langley, Christopher Potter,...
COLT
1997
Springer
14 years 24 days ago
Estimation of Time-Varying Parameters in Statistical Models: An Optimization Approach
Abstract. We propose a convex optimization approach to solving the nonparametric regression estimation problem when the underlying regression function is Lipschitz continuous. This...
Dimitris Bertsimas, David Gamarnik, John N. Tsitsi...
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
Bayesian Generalized Kernel Models
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
ML
2008
ACM
13 years 8 months ago
A linear fit gets the correct monotonicity directions
Let f be a function on Rd that is monotonic in every variable. There are 2d possible assignments to the directions of monotonicity (two per variable). We provide sufficient condit...
Malik Magdon-Ismail, Joseph Sill