Fast kernel classifiers with online and active learning

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?

Keywords

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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Publication Info

Year: 2020
Type: preprint
Citations: 627
Access: Closed

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APA Style

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