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cs.LG2022
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam, J. Zico Kolter
Owing to the prohibitive costs of generating large amounts of labeled data, programmatic weak supervision is a growing paradigm within machine learning. In this setting, users desi…
cs.LG2022
Label Propagation with Weak Supervision
Rattana Pukdee, Dylan Sam, Maria-Florina Balcan +1
Semi-supervised learning and weakly supervised learning are important paradigms that aim to reduce the growing demand for labeled data in current machine learning applications. In…