Learning from Unreliable Datasets

Manolis Zampetakis
Manolis Zampetakis

conference on learning theory, 2018.

Cited by: 0|Bibtex|Views21|

Abstract:

A wide range of learning tasks require human input in labeling massive data. The collected data though are usually low quality and contain inaccuracies and errors. As a result, modern science and business face the problem of learning from unreliable data sets.In this work, we provide a generic approach that is based on verification of onl...More

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