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» Active Learning with Model Selection in Linear Regression
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ICPR
2004
IEEE
14 years 9 months ago
Efficient Model Selection for Kernel Logistic Regression
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
Gavin C. Cawley, Nicola L. C. Talbot
ICML
2006
IEEE
14 years 9 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICML
2009
IEEE
14 years 9 months ago
Learning dictionaries of stable autoregressive models for audio scene analysis
In this paper, we explore an application of basis pursuit to audio scene analysis. The goal of our work is to detect when certain sounds are present in a mixed audio signal. We fo...
Youngmin Cho, Lawrence K. Saul
CORR
2007
Springer
164views Education» more  CORR 2007»
13 years 8 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
ISMIS
2011
Springer
12 years 11 months ago
An Evolutionary Algorithm for Global Induction of Regression Trees with Multivariate Linear Models
In the paper we present a new evolutionary algorithm for induction of regression trees. In contrast to the typical top-down approaches it globally searches for the best tree struct...
Marcin Czajkowski, Marek Kretowski