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ICPR
2006
IEEE
14 years 10 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
DATAMINE
2002
169views more  DATAMINE 2002»
13 years 9 months ago
Advances in Instance Selection for Instance-Based Learning Algorithms
The basic nearest neighbour classifier suffers from the indiscriminate storage of all presented training instances. With a large database of instances classification response time ...
Henry Brighton, Chris Mellish
SIGIR
2012
ACM
11 years 11 months ago
Active query selection for learning rankers
Methods that reduce the amount of labeled data needed for training have focused more on selecting which documents to label than on which queries should be labeled. One exception t...
Mustafa Bilgic, Paul N. Bennett
IJCNN
2007
IEEE
14 years 3 months ago
Local Learning of Tide Level Time Series using a Fuzzy Approach
— Forecasting the tide level in the Venezia lagoon is a very compelling task. In this work we propose a new approach to the learning of tide level time series based on the local ...
E. Canestrelli, P. Canestrelli, Marco Corazza, Mau...
NIPS
2003
13 years 10 months ago
Learning a Rare Event Detection Cascade by Direct Feature Selection
Face detection is a canonical example of a rare event detection problem, in which target patterns occur with much lower frequency than nontargets. Out of millions of face-sized wi...
Jianxin Wu, James M. Rehg, Matthew D. Mullin