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cs.LG2025
Self-Training: A Survey
Massih-Reza Amini, Vasilii Feofanov, Loic Pauletto +3
Semi-supervised algorithms aim to learn prediction functions from a small set of labeled observations and a large set of unlabeled observations. Because this framework is relevant…
cs.LG2024
Classification Tree-based Active Learning: A Wrapper Approach
Ashna Jose, Emilie Devijver, Massih-Reza Amini +2
Supervised machine learning often requires large training sets to train accurate models, yet obtaining large amounts of labeled data is not always feasible. Hence, it becomes cruci…