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2020 – today
- 2024
[j7]Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng
:
Online binary classification from similar and dissimilar data. Mach. Learn. 113(6): 3463-3484 (2024)- [j6]Shengjie Zhou, Senlin Shu, Haobo Wang, Hongxin Wei, Tao Xiang, Beibei Li:
Multiple-Instance Learning from Pairwise Comparison Bags. ACM Trans. Intell. Syst. Technol. 15(6): 127:1-127:22 (2024) - [j5]Jiayu Hu, Senlin Shu, Beibei Li, Tao Xiang, Zhongshi He:
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes. ACM Trans. Intell. Syst. Technol. 15(6): 131:1-131:22 (2024) - [j4]Senlin Shu, Deng-Bao Wang, Suqin Yuan, Hongxin Wei, Jiuchuan Jiang, Lei Feng, Min-Ling Zhang:
Multiple-instance Learning from Triplet Comparison Bags. ACM Trans. Knowl. Discov. Data 18(4): 90:1-90:18 (2024) - [c8]Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng:
Consistent Multi-Class Classification from Multiple Unlabeled Datasets. ICLR 2024 - [i5]Jiayu Hu, Senlin Shu, Beibei Li, Tao Xiang, Zhongshi He:
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes. CoRR abs/2409.19600 (2024) - 2023
- [j3]Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. IEEE Trans. Knowl. Data Eng. 35(11): 11599-11609 (2023) - [c7]Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng:
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. AAAI 2023: 9829-9836 - [c6]Beibei Li, Senlin Shu, Beihong Jin, Tao Xiang, Yiyuan Zheng:
Gemini: A Dual-Task Co-training Model for Partial Label Learning. AI (1) 2023: 328-340 - [i4]Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng:
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. CoRR abs/2306.06894 (2023) - 2022
- [j2]Senlin Shu, Fengmao Lv, Yan Yan, Li Li, Shuo He, Jun He:
Incorporating multiple cluster centers for multi-label learning. Inf. Sci. 590: 60-73 (2022) - [j1]Lei Feng, Jun Huang, Senlin Shu, Bo An:
Regularized Matrix Factorization for Multilabel Learning With Missing Labels. IEEE Trans. Cybern. 52(5): 3710-3721 (2022) - 2021
- [c5]Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama:
Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML 2021: 3252-3262 - [c4]Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning from Similar and Dissimilar Bags. KDD 2021: 374-382 - [i3]Yuzhou Cao, Lei Feng, Senlin Shu, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama:
Multi-Class Classification from Single-Class Data with Confidences. CoRR abs/2106.08864 (2021) - 2020
- [c3]Senlin Shu, Zhuoyi Lin, Yan Yan, Li Li:
Learning from Multi-Class Positive and Unlabeled Data. ICDM 2020: 1256-1261 - [c2]Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An:
Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020: 2206-2212 - [i2]Senlin Shu, Fengmao Lv, Lei Feng, Jun Huang, Shuo He, Jun He, Li Li:
Incorporating Multiple Cluster Centers for Multi-Label Learning. CoRR abs/2004.08113 (2020) - [i1]Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama:
Pointwise Binary Classification with Pairwise Confidence Comparisons. CoRR abs/2010.01875 (2020)
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