Nan Lu
Nan Lu
Ph.D. student, The University of Tokyo
Verified email at ms.k.u-tokyo.ac.jp
Title
Cited by
Cited by
Year
On the minimal supervision for training any binary classifier from only unlabeled data
N Lu, G Niu, AK Menon, M Sugiyama
ICLR 2019, 2018
262018
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
N Lu, T Zhang, G Niu, M Sugiyama
AISTATS 2020, 2019
112019
Rethinking Importance Weighting for Deep Learning under Distribution Shift
T Fang, N Lu, G Niu, M Sugiyama
NeurIPS 2020, 2020
42020
Pointwise Binary Classification with Pairwise Confidence Comparisons
L Feng, S Shu, N Lu, B Han, M Xu, G Niu, B An, M Sugiyama
arXiv preprint arXiv:2010.01875, 2020
2020
A One-step Approach to Covariate Shift Adaptation
T Zhang, I Yamane, N Lu, M Sugiyama
ACML 2020, 2020
2020
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Articles 1–5