Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target domain where the data distribution differs. While previous UDA methods have been ...

I’ve written several posts on different aspects of MPLS: How the FEC is key to the separation of control and forwarding functions in MPLS, the difference between implicit and explicit null labels, how ...

Label Distribution Learning (LDL) is a new learning paradigm to deal with label ambiguity and many researches have achieved the prominent performances. Compared with traditional supervised learning ...