Machine Learning with Noisy Labels

Chapter 1: Problem definition

Motivation, introduction, and challenges

Abstract

This chapter provides an informal definition of the label noise learning problem. We start by explaining how the development of robust machine learning models would be facilitated and accelerated by the successful exploration of large-scale training sets that have not been carefully annotated and consequently contain label noise. Then, we introduce the sources and models of label noise found in large-scale training sets, where we explain why label noise represents an inevitable problem in the training of machine learning models, leading to interesting challenges that are briefly discussed.

Keywords

Label noise learning; Bias-variance decomposition; Label transition methods; ...