Sheng-Jun Huang

Multi-Label Learning by Exploiting Label Correlations Locally

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the label correlations are shared by all the instances. In real-world tasks, …

Asynchronous Active Learning with Distributed Label Querying

2021

Active learning tries to learn an effective model with lowest labeling cost. Most existing active learning methods work in a synchronous way, which implies that the label querying can be performed only after the model …