Abstract

Very high dimensional learning systems become theoretically possible when training examples are abundant. The computing cost then becomes the limiting factor. Any efficient learning algorithm should at least take a brief look at each example. But should all examples be given equal attention?

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PremiseComputer scienceMachine learningArtificial intelligenceSupport vector machineLimitingKernel (algebra)Selection (genetic algorithm)Fraction (chemistry)Active learning (machine learning)Training (meteorology)Training setEmpirical researchMathematicsEngineeringStatistics

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Year
2020
Type
preprint
Citations
627
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Antoine Bordes, Şeyda Ertekin, Jason Weston et al. (2020). Fast kernel classifiers with online and active learning. .