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85
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ICCV
2007
IEEE
15 years 7 months ago
Learning The Discriminative Power-Invariance Trade-Off
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
Manik Varma, Debajyoti Ray
CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 28 days ago
Near-Optimal Bayesian Active Learning with Noisy Observations
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Daniel Golovin, Andreas Krause, Debajyoti Ray
128
Voted
CIBCB
2009
IEEE
15 years 1 months ago
Application of machine learning approaches on quantitative structure activity relationships
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
Mariusz Butkiewicz, Ralf Mueller, Danilo Selic, Er...
131
Voted
CVPR
2011
IEEE
14 years 9 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
99
Voted
ALT
2008
Springer
15 years 9 months ago
Active Learning in Multi-armed Bandits
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
András Antos, Varun Grover, Csaba Szepesv&a...