A noise- and redundancy-aware instance selection framework reduces transformer training sets by 41% on average while maintaining classification effectiveness, according to this dissertation summary.
On the cost-effectiveness of neural and non-neural approaches and repre- sentations for text classification:A comprehensive comparative study
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CTDGSI: A comprehensive exploitation of instance selection methods for automatic text classification. VII Concurso de Teses, Disserta\c{c}\~oes e Trabalhos de Gradua\c{c}\~ao em SI -- XXI Simp\'osio Brasileiro de Sistemas de Informa\c{c}\~ao
A noise- and redundancy-aware instance selection framework reduces transformer training sets by 41% on average while maintaining classification effectiveness, according to this dissertation summary.