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cs.LG2021
Rethinking Importance Weighting for Transfer Learning
Nan Lu, Tianyi Zhang, Tongtong Fang +2
A key assumption in supervised learning is that training and test data follow the same probability distribution. However, this fundamental assumption is not always satisfied in pra…
cs.LG2021★ 1 cited
Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu +2
To cope with high annotation costs, training a classifier only from weakly supervised data has attracted a great deal of attention these days. Among various approaches, strengtheni…