Senlin Shu

According to our database, Senlin Shu authored at least 19 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

iScript: A Domain-Adapted Large Language Model and Benchmark for Physical Design Tcl Script Generation.

Ning Xu, Zhaoyang Zhang, Senlin Shu, Lei Qi, Jiaqi Lv, Wensuo Wang, Tianhao Zhao, Chao Zhang, Zhaohui Yang, Xiangyu Li, Zhaorui Su, Jingshan Li, Xin Geng

CoRR, March, 2026

2025

Corrigendum: An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes.

Jiayu Hu, Senlin Shu, Beibei Li, Tao Xiang, Zhongshi He

ACM Trans. Intell. Syst. Technol., December, 2025

2024

Multiple-Instance Learning from Pairwise Comparison Bags.

Shengjie Zhou, Senlin Shu, Haobo Wang, Hongxin Wei, Tao Xiang, Beibei Li

ACM Trans. Intell. Syst. Technol., December, 2024

An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes.

Jiayu Hu, Senlin Shu, Beibei Li, Tao Xiang, Zhongshi He

ACM Trans. Intell. Syst. Technol., December, 2024

Online binary classification from similar and dissimilar data.

Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng

Mach. Learn., June, 2024

Multiple-instance Learning from Triplet Comparison Bags.

Senlin Shu, Deng-Bao Wang, Suqin Yuan, Hongxin Wei, Jiuchuan Jiang, Lei Feng, Min-Ling Zhang

ACM Trans. Knowl. Discov. Data, May, 2024

Consistent Multi-Class Classification from Multiple Unlabeled Datasets.

Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity.

Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu

IEEE Trans. Knowl. Data Eng., November, 2023

Gemini: A Dual-Task Co-training Model for Partial Label Learning.

Beibei Li, Senlin Shu, Beihong Jin, Tao Xiang, Yiyuan Zheng

Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023

A Generalized Unbiased Risk Estimator for Learning with Augmented Classes.

Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Regularized Matrix Factorization for Multilabel Learning With Missing Labels.

Lei Feng, Jun Huang, Senlin Shu, Bo An

IEEE Trans. Cybern., 2022

Incorporating multiple cluster centers for multi-label learning.

Senlin Shu, Fengmao Lv, Yan Yan, Li Li, Shuo He, Jun He

Inf. Sci., 2022

2021

Multi-Class Classification from Single-Class Data with Confidences.

Yuzhou Cao, Lei Feng, Senlin Shu, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama

CoRR, 2021

Multiple-Instance Learning from Similar and Dissimilar Bags.

Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Pointwise Binary Classification with Pairwise Confidence Comparisons.

Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Incorporating Multiple Cluster Centers for Multi-Label Learning.

Senlin Shu, Fengmao Lv, Lei Feng, Jun Huang, Shuo He, Jun He, Li Li

CoRR, 2020

Can Cross Entropy Loss Be Robust to Label Noise?

Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning from Multi-Class Positive and Unlabeled Data.

Senlin Shu, Zhuoyi Lin, Yan Yan, Li Li

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Discriminatively Relabel for Partial Multi-label Learning.

Shuo He, Ke Deng, Li Li, Senlin Shu, Li Liu

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019