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» Boosting for Regression Transfer
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ICML
2010
IEEE
10 years 3 months ago
Boosting for Regression Transfer
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
David Pardoe, Peter Stone
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
10 years 9 months ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins
NECO
2006
157views more  NECO 2006»
10 years 2 months ago
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Durga L. Shrestha, Dimitri P. Solomatine
ECML
2005
Springer
10 years 8 months ago
Combining Bias and Variance Reduction Techniques for Regression Trees
Gradient Boosting and bagging applied to regressors can reduce the error due to bias and variance respectively. Alternatively, Stochastic Gradient Boosting (SGB) and Iterated Baggi...
Yuk Lai Suen, Prem Melville, Raymond J. Mooney
COLT
2000
Springer
10 years 7 months ago
Barrier Boosting
Boosting algorithms like AdaBoost and Arc-GV are iterative strategies to minimize a constrained objective function, equivalent to Barrier algorithms. Based on this new understandi...
Gunnar Rätsch, Manfred K. Warmuth, Sebastian ...
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