Nan Lu - RankMe

23 papers A* 5A 1C 2Misc 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Learning from Ambiguous Data with Hard Labels. ICASSP Zeke Xie, Zheng He, Nan Lu, Lichen Bai, Bao Li, Shuo Yang, Mingming Sun, Ping Li
2025	J	`jnl`	Learning from Ambiguous Data with Hard Labels. CoRR Zeke Xie, Zheng He, Nan Lu, Lichen Bai, Bao Li, Shuo Yang, Mingming Sun, Ping Li
2023	J	`jnl`	A General Framework for Learning under Corruption: Label Noise, Attribute Noise, and Beyond. CoRR Laura Iacovissi, Nan Lu, Robert C. Williamson
2023	A*	`conf`	Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems. NeurIPS Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
2023	J	`jnl`	Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems. CoRR Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
2022	J	`jnl`	Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients. CoRR Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama
2022	A*	`conf`	Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients. ICLR Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama
2022	J	`jnl`	Learning from Multiple Unlabeled Datasets with Partial Risk Regularization. CoRR Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama
2022	C	`conf`	Multi-class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization. ACML Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama
2021	J	`jnl`	A One-Step Approach to Covariate Shift Adaptation. SN Comput. Sci. Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
2021	A*	`conf`	Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification. ICML Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
2021	J	`jnl`	Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification. CoRR Shida Lei, Nan Lu, Gang Niu, Issei Sato, Masashi Sugiyama
2021	A*	`conf`	Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2021	J	`jnl`	Rethinking Importance Weighting for Transfer Learning. CoRR Nan Lu, Tianyi Zhang, Tongtong Fang, Takeshi Teshima, Masashi Sugiyama
2020	C	`conf`	A One-step Approach to Covariate Shift Adaptation. ACML Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
2020	J	`jnl`	A One-step Approach to Covariate Shift Adaptation. CoRR Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
2020	A	`conf`	Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach. AISTATS Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama
2020	J	`jnl`	Pointwise Binary Classification with Pairwise Confidence Comparisons. CoRR Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2020	A*	`conf`	Rethinking Importance Weighting for Deep Learning under Distribution Shift. NeurIPS Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
2020	J	`jnl`	Rethinking Importance Weighting for Deep Learning under Distribution Shift. CoRR Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
2019	J	`jnl`	Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach. CoRR Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama
2019	—	`conf`	On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. ICLR (Poster) Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama
2018	J	`jnl`	On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data. CoRR Nan Lu, Gang Niu, Aditya Krishna Menon, Masashi Sugiyama