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» An Empirical Evaluation of LFG-DOP
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ICML
2008
IEEE
16 years 2 months ago
Confidence-weighted linear classification
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
Mark Dredze, Koby Crammer, Fernando Pereira
ICML
2005
IEEE
16 years 2 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Thomas Finley, Thorsten Joachims
ICML
2003
IEEE
16 years 2 months ago
Online Choice of Active Learning Algorithms
This paper is concerned with the question of how to online combine an ensemble of active learners so as to expedite the learning progress during a pool-based active learning sessi...
Yoram Baram, Ran El-Yaniv, Kobi Luz
ICML
2003
IEEE
16 years 2 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
ICML
2001
IEEE
16 years 2 months ago
Round Robin Rule Learning
In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is kno...
Johannes Fürnkranz