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» Training Linear Discriminant Analysis in Linear Time
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CEAS
2007
Springer
14 years 29 days ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
ECCV
2010
Springer
14 years 12 days ago
Efficient object category recognition using classemes
We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the...
AAAI
1998
13 years 10 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
INFORMATICALT
2002
116views more  INFORMATICALT 2002»
13 years 8 months ago
On the Optimization of an Adaptive State Estimation of Dynamic Systems in the Presence of Time-varying Outliers
The problem of recursive estimation of a state of dynamic systems in the presence of time-varying outliers in observations to be processed has been considered. A learning phase use...
Rimantas Pupeikis
EMNLP
2010
13 years 7 months ago
Uptraining for Accurate Deterministic Question Parsing
It is well known that parsing accuracies drop significantly on out-of-domain data. What is less known is that some parsers suffer more from domain shifts than others. We show that...
Slav Petrov, Pi-Chuan Chang, Michael Ringgaard, Hi...