Nan Lu

According to our database, Nan Lu authored at least 14 papers between 2019 and 2026.

Collaborative distances:

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

2026

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators.

Tongtong Fang, Nan Lu, Gang Niu, Kenji Fukumizu, Masashi Sugiyama

CoRR, May, 2026

2025

Learning from Ambiguous Data with Hard Labels.

Zeke Xie, Zheng He, Nan Lu, Lichen Bai, Bao Li, Shuo Yang, Mingming Sun, Ping Li

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2023

A General Framework for Learning under Corruption: Label Noise, Attribute Noise, and Beyond.

Laura Iacovissi, Nan Lu, Robert C. Williamson

CoRR, 2023

Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems.

Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning from Multiple Unlabeled Datasets with Partial Risk Regularization.

Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama

CoRR, 2022

Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients.

Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama

Proceedings of the Tenth International Conference on Learning Representations, 2022

Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization.

Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Rethinking Importance Weighting for Transfer Learning.

Nan Lu, Tianyi Zhang, Tongtong Fang, Takeshi Teshima, Masashi Sugiyama

CoRR, 2021

Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification.

Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 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

Rethinking Importance Weighting for Deep Learning under Distribution Shift.

Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach.

Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A One-step Approach to Covariate Shift Adaptation.

Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data.

Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama

Proceedings of the 7th International Conference on Learning Representations, 2019