Adaptive infinite dropout for noisy and sparse data streams

Year
2022
Private Intelligence relation
DIRECT
Link
https://scholar.google.com.vn/citations?view_op=view_citation&hl=en&user=tZ78MoQAAAAJ&citation_for_view=tZ78MoQAAAAJ:iH-uZ7U-co4C
Conference/Journal

Machine Learning 111 (8), 3025-3060

Author(s) from Distilled Foundation
Linh Ngo Van
How the work relates to Private Intelligence

A dropout mechanism to train the modeal in order to overcome various challenges regarding sparse, noisy & concept drifts in data streams

Gained Experience