This workshop is also related to the PhD work co-funded by the Fédération Charles Hermite and the French Région Grand Est “Statistical Performance Evaluation Tools for Classification and Machine Learning with Erroneous Data“.
Label Noise Problems in Statistics, Machine Learning and Classification
This workshop aims to discuss the impact that the use of partially erroneous or imprecise data can have on the evaluation, quality or relevance of classifiers and machine learning algorithms. A selection of invited speakers coming form a broad horizon covering Statistics, Machine Learning or addressing specific Classification applications will contribute to outlining research directions and statistical tools that will allow to formalise, and, hopefully, answer some of those questions.
The list of abstracts presented at the workshop is here.