Lei Feng
Lei Feng
Chongqing University / RIKEN Center for Advanced Intelligence Project
Verified email at cqu.edu.cn - Homepage
Title
Cited by
Cited by
Year
Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization
H Wei, L Feng, X Chen, B An
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 13726 …, 2020
712020
Partial Label Learning with Self-Guided Retraining
L Feng, B An
AAAI Conference on Artificial Intelligence (AAAI), 3542-3549, 2019
512019
Leveraging Latent Label Distributions for Partial Label Learning
L Feng, B An
International Joint Conference on Artificial Intelligence (IJCAI), 2107-2113, 2018
442018
Collaboration based Multi-Label Learning
L Feng, B An, S He
AAAI Conference on Artificial Intelligence (AAAI), 3550-3557, 2019
322019
Partial Label Learning by Semantic Difference Maximization
L Feng, B An
International Joint Conference on Artificial Intelligence (IJCAI), 2294-2300, 2019
322019
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
282017
Learning with Multiple Complementary Labels
L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama
International Conference on Machine Learning (ICML), 3072-3081, 2020
262020
Progressive Identification of True Labels for Partial-Label Learning
J Lv, M Xu, L Feng, G Niu, X Geng, M Sugiyama
International Conference on Machine Learning (ICML), 6500-6510, 2020
252020
Can Cross Entropy Loss be Robust to Label Noise?
L Feng, S Shu, Z Lin, F Lv, L Li, B An
International Joint Conference on Artificial Intelligence (IJCAI), 2206-2212, 2020
192020
Provably Consistent Partial-Label Learning
L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama
Advances in Neural Information Processing Systems (NeurIPS), 10948-10960, 2020
152020
Estimating Latent Relative Labeling Importances for Multi-Label Learning
S He, L Feng, L Li
IEEE International Conference on Data Mining (ICDM), 1013-1018, 2018
82018
Semi-Supervised Classification using Multiple Clusterings
G Yu, L Feng, G Yao, J Wang
Pattern Recognition and Image Analysis 26 (4), 681-687, 2016
52016
Pointwise Binary Classification with Pairwise Confidence Comparisons
L Feng, S Shu, N Lu, B Han, M Xu, G Niu, B An, M Sugiyama
International Conference on Machine Learning (ICML), 3252-3262, 2021
32021
Fast Top-N Personalized Recommendation on Item Graph
Z Lin, L Feng, C Xu, CK Kwoh
IEEE International Conference on Big Data (BigData), 3903-3908, 2019
32019
Learning from Similarity-Confidence Data
Y Cao, L Feng, Y Xu, B An, G Niu, M Sugiyama
International Conference on Machine Learning (ICML), 1272-1282, 2021
22021
Incorporating Multiple Cluster Centers for Multi-Label Learning
S Shu, F Lv, L Feng, Y Yan, S He, J He, L Li
arXiv preprint arXiv:2004.08113, 2020
22020
Regularized Matrix Factorization for Multilabel Learning With Missing Labels
L Feng, J Huang, S Shu, B An
IEEE Transactions on Cybernetics, 2020
22020
Semi-Supervised Classification Based on Mixture Graph
L Feng, G Yu
Algorithms 8 (4), 1021-1034, 2015
22015
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
arXiv preprint arXiv:2012.00925, 2020
12020
Learning Cross-domain Semantic-Visual Relation for Transductive Zero-Shot Learning
J Zhang, F Lv, G Yang, L Feng, Y Yu, L Duan
arXiv preprint arXiv:2003.14105, 2020
12020
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Articles 1–20