This article reports an empirical investigation of the accuracy of rules that classify examples on the basis of a single attribute. On most datasets studied, the best of these very simple rules is as accurate as the rules induced by the majority of machine learning systems. The article explores the implications of this finding for machine learning research and applications.
Feb 15th 2022
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chair Osmar Zaiane: UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-Wise Perspective with Transformer
Sep 27th 2021
Sep 17th 2021
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