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ICML
2009
IEEE
16 years 7 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
ICML
2006
IEEE
16 years 7 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
AIIA
2007
Springer
15 years 8 months ago
Tonal Harmony Analysis: A Supervised Sequential Learning Approach
We have recently presented CarpeDiem, an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. CarpeDiem provides impress...
Daniele P. Radicioni, Roberto Esposito

Book
519views
17 years 5 months ago
Information Theory, Inference, and Learning Algorithms
This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...
David J. C. MacKay
ACL
2009
15 years 4 months ago
Learning foci for Question Answering over Topic Maps
This paper introduces the concepts of asking point and expected answer type as variations of the question focus. They are of particular importance for QA over semistructured data,...
Alexander Mikhailian, Tiphaine Dalmas, Rani Pinchu...