Bo Han
Bo Han
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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
NeurIPS 2018, 2018
How does Disagreement Help Generalization against Label Corruption?
X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama
ICML 2019, 2019
Masking: A New Perspective of Noisy Supervision
B Han, J Yao, G Niu, M Zhou, IW Tsang, Z Ya, M Sugiyama
NeurIPS 2018, 2018
Are Anchor Points Really Indispensable in Label-Noise Learning?
X Xia, T Liu, N Wang, B Han, C Gong, G Niu, M Sugiyama
NeurIPS 2019, 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
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
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent
B Han, IW Tsang, L Chen
ECML 2016, 2016
Towards Robust ResNet: A Small Step but A Giant Leap
J Zhang, B Han, L Wynter, KH Low, M Kankanhalli
IJCAI 2019, 2019
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
Q Yao, JT Kwok, B Han
ICML 2019, 2019
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
Robust Plackett–Luce Model for k-ary Crowdsourced Preferences
B Han, Y Pan, IW Tsang
Machine Learning Journal, 2017
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
Learning from Multiple Complementary Labels
L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama
ICML 2020, 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
J Zhang, X Xu, B Han, G Niu, L Cui, M Sugiyama, M Kankanhalli
ICML 2020, 2020
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
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
Confidence Scores Make Instance-dependent Label-noise Learning Possible
A Berthon, B Han, G Niu, T Liu, M Sugiyama
arXiv preprint arXiv:2001.03772, 2020
Stagewise Learning for Noisy k-ary Preferences
Y Pan, B Han, IW Tsang
Machine Learning Journal, 2017
Provably Consistent Partial-Label Learning
L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama
NeurIPS 2020, 2020
Parts-dependent Label Noise: Towards Instance-dependent Label Noise
X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama
NeurIPS 2020, 2020
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