Bo Han
Bo Han
HKBU / RIKEN
Verified email at comp.hkbu.edu.hk
Title
Cited by
Cited by
Year
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
B Han, Q Yao, X Yu, G Niu, M Xu, W Hu, IW Tsang, M Sugiyama
Advances in Neural Information Processing Systems, 2018
1562018
Masking: A New Perspective of Noisy Supervision
B Han, J Yao, G Niu, M Zhou, IW Tsang, Z Ya, M Sugiyama
Advances in Neural Information Processing Systems, 2018
392018
How does Disagreement Help Generalization against Label Corruption?
X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama
International Conference on Machine Learning, 2019
25*2019
Progressive Stochastic Learning for Noisy Labels
B Han, IW Tsang, L Chen, C Yu, SF Fung
IEEE Transactions on Neural Networks and Learning Systems, 2017
182017
Fast Image Recognition based on Independent Component Analysis
S Zhang, B He, R Nian, J Wang, B Han, A Lendasse, G Yuan
Cognitive Computation, 2014
172014
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent
B Han, IW Tsang, L Chen
European Conference on Machine Learning, 2016
132016
LARSEN: Selective Ensemble Learning using LARS for Blended Data
B Han, B He, R Nian, M Ma, S Zhang, M Li, A Lendasse
Neurocomputing, 2015
12*2015
Robust Plackett–Luce Model for k-ary Crowdsourced Preferences
B Han, Y Pan, IW Tsang
Machine Learning Journal, 2017
92017
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
Q Yao, JT Kwok, B Han
International Conference on Machine Learning, 2019
8*2019
HSR: L 1/2-regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
B Han, B He, T Sun, T Yan, M Ma, Y Shen, A Lendasse
Neural Computing and Applications, 2015
82015
Are Anchor Points Really Indispensable in Label-Noise Learning?
X Xia, T Liu, N Wang, B Han, C Gong, G Niu, M Sugiyama
Advances in Neural Information Processing Systems, 2019
72019
Towards Robust ResNet: A Small Step but A Giant Leap
J Zhang, B Han, L Wynter, KH Low, M Kankanhalli
International Joint Conference on Artificial Intelligence, 2019
62019
Matrix Co-completion for Multi-label Classification with Missing Features and Labels
M Xu, G Niu, B Han, IW Tsang, ZH Zhou, M Sugiyama
arXiv preprint arXiv:1805.09156, 2018
52018
Stagewise Learning for Noisy k-ary Preferences
Y Pan, B Han, IW Tsang
Machine Learning Journal, 2017
32017
Butterfly: A Panacea for All Difficulties in Wildly Unsupervised Domain Adaptation
F Liu, J Lu, B Han, G Niu, G Zhang, M Sugiyama
arXiv preprint arXiv:1905.07720 presented at NeurIPS19 workshop, 2019
22019
Learning from Multiple Complementary Labels
L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama
arXiv preprint arXiv:1912.12927, 2019
12019
Privacy-preserving Stochastic Gradual Learning
B Han, IW Tsang, X Xiao, L Chen, S Fung, CP Yu
IEEE Transactions on Knowledge and Data Engineering, 2019
12019
A Meta Approach to Robust Deep Learning with Noisy Labels
B Han, G Niu, J Yao, X Yu, M Xu, I Tsang, M Sugiyama
arXiv preprint arXiv:1809.11008 presented at ICML19 workshop, 2018
1*2018
Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels
B Han, IW Tsang, L Chen, JT Zhou, C Yu
IEEE Transactions on Neural Networks and Learning Systems, 2016
12016
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
J Zhang, X Xu, B Han, G Niu, L Cui, M Sugiyama, M Kankanhalli
arXiv preprint arXiv:2002.11242, 2020
2020
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