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JMLR
2010
130views more  JMLR 2010»
14 years 4 months ago
A Regularization Approach to Nonlinear Variable Selection
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
JMLR
2010
129views more  JMLR 2010»
14 years 4 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
88
Voted
JMLR
2010
110views more  JMLR 2010»
14 years 4 months ago
Nonlinear functional regression: a functional RKHS approach
This paper deals with functional regression, in which the input attributes as well as the response are functions. To deal with this problem, we develop a functional reproducing ke...
Hachem Kadri, Emmanuel Duflos, Philippe Preux, St&...
JMLR
2010
84views more  JMLR 2010»
14 years 4 months ago
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
The versatility of exponential families, along with their attendant convexity properties, make them a popular and effective statistical model. A central issue is learning these mo...
Sham Kakade, Ohad Shamir, Karthik Sindharan, Ambuj...
76
Voted
JMLR
2010
130views more  JMLR 2010»
14 years 4 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...