ICML
|
2021

Adversarial Multiclass Learning under Weak Supervision with Performance Guarantees

Abstract

This paper presents a rigorous approach for using a set of arbitrarily correlated weak supervision sources in order to solve a multiclass classification task when only a very small set of labeled data is available

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