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ORCIDMachine Learning, Volume 51, 2003
Volume 51, Number 1, April 2003
- David A. McAllester:
PAC-Bayesian Stochastic Model Selection. 5-21 - Jürgen Forster, Manfred K. Warmuth:
Relative Loss Bounds for Temporal-Difference Learning. 23-50 - Don R. Hush, Clint Scovel:
Polynomial-Time Decomposition Algorithms for Support Vector Machines. 51-71 - Terran Lane, Carla E. Brodley:
An Empirical Study of Two Approaches to Sequence Learning for Anomaly Detection. 73-107
Volume 51, Number 2, May 2003
- Gareth James:
Variance and Bias for General Loss Functions. 115-135 - Dana Angluin, Martins Krikis:
Learning from Different Teachers. 137-163 - John Langford, Avrim Blum:
Microchoice Bounds and Self Bounding Learning Algorithms. 165-179 - Ludmila I. Kuncheva
, Christopher J. Whitaker:
Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. 181-207
Volume 51, Number 3, June 2003
- Claudio Gentile:
Guest Editor's Introduction. 215-216 - Adam R. Klivans, Rocco A. Servedio:
Boosting and Hard-Core Set Construction. 217-238 - Nicolò Cesa-Bianchi, Gábor Lugosi:
Potential-Based Algorithms in On-Line Prediction and Game Theory. 239-261 - Jürgen Forster, Niels Schmitt, Hans Ulrich Simon, Thorsten Suttorp:
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces. 263-281 - Sanjoy Dasgupta, Wee Sun Lee, Philip M. Long:
A Theoretical Analysis of Query Selection for Collaborative Filtering. 283-298
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