EuroCC2's national competence center in Sweden (ENCCS) is organizing a webinar on the development of algorithms for partial multi-label machine learning on 15 April 2025.
Machine learning is a branch of artificial intelligence that allows computers to learn from data and make predictions or decisions without being explicitly programmed. Multi-label learning is a specific type of machine learning problem in which each data instance can be assigned multiple labels simultaneously. Partial multi-label learning deals with scenarios where each instance is provided with a candidate set of labels, but only a subset of those labels is accurate.
This webinar will address the general features of various partial multi-label methods. The discussion will also cover the development of learning algorithms aimed at managing datasets that contain a significant number of noisy labels across different domains, utilizing various frameworks. The focus will be on recently developed methods for partial multi-label learning based on the Encoder-Decoder framework.
