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ORCIDNing Xu 0009
Person information
- affiliation: Southeast University, School of Computer Science and Engineering, MOE Key Laboratory of Computer Network and Information Integration, Nanjing, China
Other persons with the same name
- Ning Xu — disambiguation page
- Ning Xu 0001 — Amazon Go, USA (and 1 more)
- Ning Xu 0002
![[0000-0002-0077-751X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-0077-751X")
— Hohai University, Changzhou Key College of Internet of Things Engineering, Changzhou, China - Ning Xu 0003 — Tianjin University, Tianjin, China
- Ning Xu 0004 — Northeastern University, Shenyang, China
- Ning Xu 0005 — Samsung Electronics America, Inc. (and 1 more)
- Ning Xu 0006 — Wuhan University of Technology, Wuhan, China
- Ning Xu 0007 — Adobe Research, San Jose, CA, USA (and 2 more)
- Ning Xu 0008 — University of Chinese Academy of Sciences, Beijing, China
- Ning Xu 0010 — Snap Inc., Venice, CA, USA
- Ning Xu 0011 — Vanderbilt University, Nashville, TN, USA (and 1 more)
- Ning Xu 0012 — Liaoning Shihua University, Fushun, China (and 1 more)
- Ning Xu 0013 — Bohai University, College of Information Science and Technology, China (and 1 more)
- Ning Xu 0014 — China University of Petroleum-Beijing, Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China
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2020 – today
- 2024
[j13]Jiaqi Lv, Biao Liu, Lei Feng, Ning Xu, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama:
On the Robustness of Average Losses for Partial-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 2569-2583 (2024)- [j12]Hao Gu, Jian Gu, Keyu Peng, Ziran Zhu, Ning Xu, Xin Geng, Jun Yang:
LAMPlace: Legalization-Aided Reinforcement Learning-Based Macro Placement for Mixed-Size Designs With Preplaced Blocks. IEEE Trans. Circuits Syst. II Express Briefs 71(8): 3770-3774 (2024) - [j11]Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng:
Variational Continuous Label Distribution Learning for Multi-Label Text Classification. IEEE Trans. Knowl. Data Eng. 36(6): 2716-2729 (2024) - [c27]Biao Liu, Congyu Qiao, Ning Xu, Xin Geng, Ziran Zhu, Jun Yang:
Variational Label-Correlation Enhancement for Congestion Prediction. ASPDAC 2024: 466-471 - [c26]Ning Xu, Yihao Hu, Congyu Qiao, Xin Geng:
Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning. ICML 2024 - [c25]Biao Liu, Ning Xu, Xiangyu Fang, Xin Geng:
Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning. ICML 2024 - [c24]Yangfan Liu, Jiaqi Lv, Xin Geng, Ning Xu:
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency. ICML 2024 - [c23]Congyu Qiao, Ning Xu, Yihao Hu, Xin Geng:
ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision. ICML 2024 - [i13]Biao Liu, Ning Xu, Xin Geng:
Progressively Selective Label Enhancement for Language Model Alignment. CoRR abs/2408.02599 (2024) - 2023
- [j10]Ning Xu, Jun Shu, RenYi Zheng, Xin Geng, Deyu Meng, Min-Ling Zhang:
Variational Label Enhancement. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 6537-6551 (2023) - [j9]Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng:
Continuous label distribution learning. Pattern Recognit. 133: 109056 (2023) - [j8]Ke Wang, Ning Xu, Miaogen Ling, Xin Geng:
Fast Label Enhancement for Label Distribution Learning. IEEE Trans. Knowl. Data Eng. 35(2): 1502-1514 (2023) - [j7]Ning Xu, Yong-Di Wu, Congyu Qiao, Yi Ren, Minxue Zhang, Xin Geng:
Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement. IEEE Trans. Knowl. Data Eng. 35(11): 11656-11667 (2023) - [j6]Ning Xu, Yun-Peng Liu, Yan Zhang, Xin Geng:
Progressive Enhancement of Label Distributions for Partial Multilabel Learning. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4856-4867 (2023) - [j5]Ning Xu, Jia-Yu Li, Yun-Peng Liu, Xin Geng:
Trusted-Data-Guided Label Enhancement on Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 34(12): 9940-9951 (2023) - [c22]Xingyu Zhao, Yuexuan An, Ning Xu, Jing Wang, Xin Geng:
Imbalanced Label Distribution Learning. AAAI 2023: 11336-11344 - [c21]Shiyu Xia, Jiaqi Lv, Ning Xu, Gang Niu, Xin Geng:
Towards Effective Visual Representations for Partial-Label Learning. CVPR 2023: 15589-15598 - [c20]Congyu Qiao, Ning Xu, Xin Geng:
Decompositional Generation Process for Instance-Dependent Partial Label Learning. ICLR 2023 - [c19]Biao Liu, Ning Xu, Jiaqi Lv, Xin Geng:
Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. ICML 2023: 22249-22265 - [c18]Congyu Qiao, Ning Xu, Jiaqi Lv, Yi Ren, Xin Geng:
FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning. ICML 2023: 28321-28336 - [c17]Ning Xu, Biao Liu, Jiaqi Lv, Congyu Qiao, Xin Geng:
Progressive Purification for Instance-Dependent Partial Label Learning. ICML 2023: 38551-38565 - [c16]Yu Shi, Ning Xu, Hua Yuan, Xin Geng:
Unreliable Partial Label Learning with Recursive Separation. IJCAI 2023: 4208-4216 - [c15]Hua Yuan, Yu Shi, Ning Xu, Xu Yang, Xin Geng, Yong Rui:
Learning From Biased Soft Labels. NeurIPS 2023 - [i12]Hua Yuan, Ning Xu, Yu Shi, Xin Geng, Yong Rui:
Learning From Biased Soft Labels. CoRR abs/2302.08155 (2023) - [i11]Yu Shi, Ning Xu, Hua Yuan, Xin Geng:
Unreliable Partial Label Learning with Recursive Separation. CoRR abs/2302.09891 (2023) - [i10]Shiyu Xia, Jiaqi Lv, Ning Xu, Gang Niu, Xin Geng:
Towards Effective Visual Representations for Partial-Label Learning. CoRR abs/2305.06080 (2023) - [i9]Biao Liu, Congyu Qiao, Ning Xu, Xin Geng, Ziran Zhu, Jun Yang:
Variational Label-Correlation Enhancement for Congestion Prediction. CoRR abs/2308.00529 (2023) - [i8]Biao Liu, Jie Wang, Ning Xu, Xin Geng:
Can Class-Priors Help Single-Positive Multi-Label Learning? CoRR abs/2309.13886 (2023) - 2022
- [j4]Yi Ren, Ning Xu, Miaogen Ling, Xin Geng:
Label distribution for multimodal machine learning. Frontiers Comput. Sci. 16(1): 161306 (2022) - [j3]Minxue Zhang, Ning Xu, Xin Geng:
Feature-Induced Label Distribution for Learning with Noisy Labels. Pattern Recognit. Lett. 155: 107-113 (2022) - [c14]Qiu-Feng Wang, Xin Geng, Shuxia Lin, Shiyu Xia, Lei Qi, Ning Xu:
Learngene: From Open-World to Your Learning Task. AAAI 2022: 8557-8565 - [c13]Shiyu Xia, Jiaqi Lv, Ning Xu, Xin Geng:
Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning. IJCAI 2022: 3615-3621 - [c12]Xingyu Zhao, Yuexuan An, Ning Xu, Xin Geng:
Fusion Label Enhancement for Multi-Label Learning. IJCAI 2022: 3773-3779 - [c11]Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang:
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. NeurIPS 2022 - [i7]Congyu Qiao, Ning Xu, Xin Geng:
Decomposition-based Generation Process for Instance-Dependent Partial Label Learning. CoRR abs/2204.03845 (2022) - [i6]Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang:
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. CoRR abs/2206.00517 (2022) - [i5]Ning Xu, Jiaqi Lv, Biao Liu, Congyu Qiao, Xin Geng:
Progressive Purification for Instance-Dependent Partial Label Learning. CoRR abs/2206.00830 (2022) - 2021
- [j2]Jiaqi Lv, Tianran Wu, Cheng-Lun Peng, Yunpeng Liu, Ning Xu, Xin Geng:
Compact learning for multi-label classification. Pattern Recognit. 113: 107833 (2021) - [j1]Ning Xu, Yun-Peng Liu, Xin Geng:
Label Enhancement for Label Distribution Learning. IEEE Trans. Knowl. Data Eng. 33(4): 1632-1643 (2021) - [c10]Yongbiao Gao, Ning Xu, Xin Geng:
Video Summarization via Label Distributions Dual-Reward. IJCAI 2021: 2403-2409 - [c9]Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang:
Instance-Dependent Partial Label Learning. NeurIPS 2021: 27119-27130 - [i4]Qiufeng Wang, Xin Geng, Shuxia Lin, Shiyu Xia, Lei Qi, Ning Xu:
Learngene: From Open-World to Your Learning Task. CoRR abs/2106.06788 (2021) - [i3]Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang:
Instance-Dependent Partial Label Learning. CoRR abs/2110.12911 (2021) - 2020
- [c8]Ning Xu, Yun-Peng Liu, Xin Geng:
Partial Multi-Label Learning with Label Distribution. AAAI 2020: 6510-6517 - [c7]Ning Xu, Jun Shu, Yun-Peng Liu, Xin Geng:
Variational Label Enhancement. ICML 2020: 10597-10606 - [c6]Yun-Peng Liu, Ning Xu, Yu Zhang, Xin Geng:
Label Distribution for Learning with Noisy Labels. IJCAI 2020: 2568-2574 - [i2]Jiaqi Lv, Tianran Wu, Cheng-Lun Peng, Yunpeng Liu, Ning Xu, Xin Geng:
Compact Learning for Multi-Label Classification. CoRR abs/2009.08607 (2020)
2010 – 2019
- 2019
- [c5]Ning Xu, Jiaqi Lv, Xin Geng:
Partial Label Learning via Label Enhancement. AAAI 2019: 5557-5564 - [c4]Jiaqi Lv, Ning Xu, RenYi Zheng, Xin Geng:
Weakly Supervised Multi-Label Learning via Label Enhancement. IJCAI 2019: 3101-3107 - 2018
- [c3]Ruifeng Shao, Ning Xu, Xin Geng:
Multi-label Learning with Label Enhancement. ICDM 2018: 437-446 - [c2]Ning Xu, An Tao, Xin Geng:
Label Enhancement for Label Distribution Learning. IJCAI 2018: 2926-2932 - [c1]An Tao, Ning Xu, Xin Geng:
Labeling Information Enhancement for Multi-label Learning with Low-Rank Subspace. PRICAI (1) 2018: 671-683 - 2017
- [i1]Ruifeng Shao, Xin Geng, Ning Xu:
Multi-Label Learning with Label Enhancement. CoRR abs/1706.08323 (2017)
Coauthor Index
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