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ICML
1999
IEEE
14 years 5 months ago
Machine-Learning Applications of Algorithmic Randomness
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
Volodya Vovk, Alexander Gammerman, Craig Saunders
ICML
1999
IEEE
14 years 5 months ago
AdaCost: Misclassification Cost-Sensitive Boosting
AdaCost, a variant of AdaBoost, is a misclassification cost-sensitive boosting method. It uses the cost of misclassifications to update the training distribution on successive boo...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip...
ICML
1999
IEEE
14 years 5 months ago
Approximation Via Value Unification
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
Paul E. Utgoff, David J. Stracuzzi
ICML
2006
IEEE
14 years 5 months ago
Robust probabilistic projections
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
Cédric Archambeau, Michel Verleysen, Nicola...
ICML
2000
IEEE
13 years 9 months ago
Discriminative Reranking for Natural Language Parsing
This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with assoc...
Michael Collins