Multi-view positive and unlabeled learning

• Main Authors: Zhou, Joey Tianyi, Pan, Sinno Jialin, Mao, Qi, Tsang, Ivor W.
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/106283; http://hdl.handle.net/10220/24004; http://jmlr.org/proceedings/papers/v25/zhou12/zhou12.pdf
• Institution: Nanyang Technological University

Learning with Positive and Unlabeled instances (PU learning) arises widely in information retrieval applications. To address the unavailability issue of negative instances, most existing PU learning approaches require to either identify a reliable set of negative instances from the unlabeled data or...