Manuel Roveri: "Is Tiny Deep Learning the new Deep Learning?”

16H00-16H15 (UTC): Alessio Bernardo, Emanuele Della Valle, and Albert Bifet,

“Incremental Rebalancing Learning on Evolving Data Streams”

16H15-16H30 (UTC): Giacomo Ziffer, Emanuele Della Valle, Alessio Bernardo, and Albert Bifet,

“Fast Incremental Naïve Bayes with Kalman Filtering”

16H30-16H45 (UTC): Alexandre Abraham and Léo Dreyfus-Schmidt,

“Rebuilding Trust in Active Learning with Actionable Metrics”

16H45-17H00 (UTC): Parsa Vafaie, Herna Viktor, and Wojtek Michalowski,

“Multi-class imbalanced semi-supervised learning from streams through online ensembles”

17H15-17H30 (UTC): Shujie Yin, Guanjun Liu, Zhenchuan Li, Chungang Yan, and Changjun Jiang,

“An Accuracy-and-Diversity-based Ensemble Method for Concept Drift and Its application in Fraud Detection”

17H30-17H45 (UTC): Zoltan Puha, Maurits Kaptein, and Aurelie Lemmens,

"Batch Mode Active Learning for Individual Treatment Effect Estimation"

17H45-18H00 (UTC): Tengyue Li, Simon Fong, Yaoyang Wu, and Antonio J. Tallón Ballesteros,

"Kennard-Stone Balance Algorithm for Time-series Big Data Stream Mining"