IEEE

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation

Abstract: Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones. In SSPLL, the ...
IEEE

Partial Domain Adaptation in Remaining Useful Life Prediction With Incomplete Target Data

Abstract: Intelligent machinery prognostics and health management (PHM) methods have been attracting growing attention in the past years, with the rapid development of the artificial intelligence ...
Seeking Alpha

Morgan Stanley weighs partial reduction in data-center exposure via SRT - report

Morgan Stanley (MS) is weighing reducing some of its exposure to AI data centers, having held initial discussions with potential investors about a so-called significant risk transfer ("SRT") linked to ...
BMJ

Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies

Objective To identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and ...