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98
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ICML
2009
IEEE
16 years 1 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer
CEC
2008
IEEE
15 years 7 months ago
The simplest evolution/learning hybrid: LEM with KNN
Abstract— The Learnable Evolution Model (LEM) was introduced by Michalski in 2000, and involves interleaved bouts of evolution and learning. Here we investigate LEM in (we think)...
Guleng Sheri, David W. Corne
COLT
1992
Springer
15 years 4 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
ML
2000
ACM
103views Machine Learning» more  ML 2000»
15 years 18 days ago
Phase Transitions in Relational Learning
One of the major limitations of relational learning is due to the complexity of verifying hypotheses on examples. In this paper we investigate this task in light of recent publishe...
Attilio Giordana, Lorenza Saitta
101
Voted
ICML
2009
IEEE
16 years 1 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas