Han Bao
Han Bao
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Imitation Learning from Imperfect Demonstration
YH Wu, N Charoenphakdee, H Bao, V Tangkaratt, M Sugiyama
ICML 2019, 2019
Classification from Pairwise Similarity and Unlabeled Data
H Bao, G Niu, M Sugiyama
ICML 2018, 2018
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
S Kuroki, N Charoenphakdee, H Bao, J Honda, I Sato, M Sugiyama
AAAI 2019, 2019
Calibrated Surrogate Losses for Adversarially Robust Classification
H Bao, C Scott, M Sugiyama
COLT 2020, 2020
Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization
T Shimada, H Bao, I Sato, M Sugiyama
Neural Computation, 2021
Pairwise supervision can provably elicit a decision boundary
H Bao, T Shimada, L Xu, I Sato, M Sugiyama
AISTATS 2022, 2022
On the surrogate gap between contrastive and supervised losses
H Bao, Y Nagano, K Nozawa
International Conference on Machine Learning, 1585-1606, 2022
Machine learning from weak supervision: An empirical risk minimization approach
M Sugiyama, H Bao, T Ishida, N Lu, T Sakai, G Niu
MIT Press, 2022
Convex Formulation of Multiple Instance Learning from Positive and Unlabeled Bags
H Bao, T Sakai, I Sato, M Sugiyama
Neural Networks 105, 132-141, 2018
Will Large-scale Generative Models Corrupt Future Datasets?
R Hataya, H Bao, H Arai
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
H Bao, M Sugiyama
AISTATS 2020, 2020
Calibrated Surrogate Maximization of Dice
M Nordström, H Bao, F Löfman, H Hult, A Maki, M Sugiyama
MICCAI 2020, 269-278, 2020
Momentum tracking: Momentum acceleration for decentralized deep learning on heterogeneous data
Y Takezawa, H Bao, K Niwa, R Sato, M Yamada
arXiv preprint arXiv:2209.15505, 2022
Approximating 1-wasserstein distance with trees
M Yamada, Y Takezawa, R Sato, H Bao, Z Kozareva, S Ravi
arXiv preprint arXiv:2206.12116, 2022
Learning from noisy similar and dissimilar data
S Dan, H Bao, M Sugiyama
Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021
Necessary and sufficient watermark for large language models
Y Takezawa, R Sato, H Bao, K Niwa, M Yamada
arXiv preprint arXiv:2310.00833, 2023
Unbalanced optimal transport for unbalanced word alignment
Y Arase, H Bao, S Yokoi
arXiv preprint arXiv:2306.04116, 2023
Embarrassingly simple text watermarks
R Sato, Y Takezawa, H Bao, K Niwa, M Yamada
arXiv preprint arXiv:2310.08920, 2023
Sparse Regularized Optimal Transport with Deformed q-Entropy
H Bao, S Sakaue
Entropy 24 (11), 1634, 2022
Beyond exponential graph: Communication-efficient topologies for decentralized learning via finite-time convergence
Y Takezawa, R Sato, H Bao, K Niwa, M Yamada
Advances in Neural Information Processing Systems 36, 2024
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