Lei Feng
Lei Feng
Other namesFeng Lei
Chongqing University / RIKEN Center for Advanced Intelligence Project
Verified email at - Homepage
Cited by
Cited by
Combating noisy labels by agreement: A joint training method with co-regularization
H Wei, L Feng, X Chen, B An
CVPR 2020, 13726-13735, 2020
Partial label learning with self-guided retraining
L Feng, B An
AAAI 2019, 3542-3549, 2019
Can Cross Entropy Loss be Robust to Label Noise?
L Feng, S Shu, Z Lin, F Lv, L Li, B An
IJCAI 2020, 2206-2212, 2020
Progressive Identification of True Labels for Partial-Label Learning
J Lv, M Xu, L Feng, G Niu, X Geng, M Sugiyama
ICML 2020, 6500-6510, 2020
Leveraging Latent Label Distributions for Partial Label Learning
L Feng, B An
IJCAI 2018, 2107-2113, 2018
Partial Label Learning by Semantic Difference Maximization
L Feng, B An
IJCAI 2019, 2294-2300, 2019
Provably Consistent Partial-Label Learning
L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama
NeurIPS 2020, 10948-10960, 2020
Collaboration based Multi-Label Learning
L Feng, B An, S He
AAAI 2019, 3550-3557, 2019
Learning with Multiple Complementary Labels
L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama
ICML 2020, 3072-3081, 2020
A Driving Behavior Detection System based on a Smartphone's Built‐in Sensor
Y Li, F Xue, L Feng, Z Qu
International Journal of Communication Systems 30 (8), 1-13, 2017
PiCO: Contrastive Label Disambiguation for Partial Label Learning
H Wang, R Xiao, Y Li, L Feng, G Niu, G Chen, J Zhao
ICLR 2022, 2022
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
L Tao, L Feng, J Yi, S Huang, S Chen
NeurIPS 2021, 16209-16225, 2021
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence
D Wang, L Feng, M Zhang
NeurIPS 2021, 11809-11820, 2021
Mitigating Neural Network Overconfidence with Logit Normalization
H Wei, R Xie, H Cheng, L Feng, B An, S Li
ICML 2022, 2022
Estimating Latent Relative Labeling Importances for Multi-Label Learning
S He, L Feng, L Li
ICDM 2018, 1013-1018, 2018
Regularized Matrix Factorization for Multilabel Learning With Missing Labels
L Feng, J Huang, S Shu, B An
IEEE Transactions on Cybernetics 52 (5), 3710-3721, 2022
Attention is not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion
T Liang, G Lin, L Feng, Y Zhang, F Lv
ICCV 2021, 8148-8156, 2021
Seminll: A framework of noisy-label learning by semi-supervised learning
Z Wang, J Jiang, B Han, L Feng, B An, G Niu, G Long
Transactions on Machine Learning Research, 2022
Pointwise Binary Classification with Pairwise Confidence Comparisons
L Feng, S Shu, N Lu, B Han, M Xu, G Niu, B An, M Sugiyama
ICML 2021, 3252-3262, 2021
Partial Multi-label Learning with Mutual Teaching
Y Yan, S Li, L Feng
Knowledge-Based Systems, 2020
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