Deep learning for noise-tolerant RDFS reasoning

author: James A. Hendler, Rensselaer Polytechnic Institute
published: Dec. 10, 2019,   recorded: October 2019,   views: 4


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Comment1 Henry Fielding, February 18, 2022 at 11:31 a.m.:

In general, there are two main approaches to noise in data: (1) data cleaning and (2) robust learning. The former aims at removing the noise from the data, while the latter directly builds models that tolerate noisy instances. Being a student, I often visit to find a good writer good enough to meet my needs.

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