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SIGIR
2012
ACM
13 years 9 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
KDD
2004
ACM
187views Data Mining» more  KDD 2004»
16 years 7 months ago
IMMC: incremental maximum margin criterion
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
CVPR
2010
IEEE
16 years 2 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
CEC
2009
IEEE
16 years 1 months ago
On-line neuroevolution applied to The Open Racing Car Simulator
— The application of on-line learning techniques to modern computer games is a promising research direction. In fact, they can be used to improve the game experience and to achie...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
DSMML
2004
Springer
16 years 20 hour ago
Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
Peter Sollich