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ORCIDYongli Mou
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2020 – today
- 2024
[j2]Feifei Li, Yongli Mou
, Zeyu Zhang, Quan Liu, Sabina Jeschke:
A novel model for the pavement distress segmentation based on multi-level attention DeepLabV3+. Eng. Appl. Artif. Intell. 137: 109175 (2024)- [j1]Jiahui Geng, Yongli Mou, Qing Li, Feifei Li, Oya Beyan, Stefan Decker, Chunming Rong:
Improved Gradient Inversion Attacks and Defenses in Federated Learning. IEEE Trans. Big Data 10(6): 839-850 (2024) - [c11]Yixin Peng, Yongli Mou, Bozhen Zhu, Sulayman K. Sowe, Stefan Decker:
RWTH-DBIS at LLMs4OL 2024 Tasks A and B Knowledge-Enhanced Domain-Specific Continual Learning and Prompt-Tuning of Large Language Models for Ontology Learning. LLMs4OL@ISWC 2024: 49-63 - [c10]Yongli Mou, Jonathan Lehmkuhl, Nicolas Sauerbrunn, Anja Köchel, Jens Panse, Daniel Truh, Sulayman K. Sowe, Tim H. Brümmendorf, Stefan Decker:
Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study. MIE 2024: 685-689 - [c9]Yongli Mou, Li Liu, Sulayman K. Sowe, Diego Collarana, Stefan Decker:
Leveraging LLMs Few-shot Learning to Improve Instruction-driven Knowledge Graph Construction. VLDB Workshops 2024 - 2023
- [c8]Yongli Mou, Feifei Li, Sven Weber, Sabith Haneef, Hans Meine, Liliana Caldeira, Mehrshad Jaberansary, Sascha Welten, Yeliz Ucer Yediel, Guido P. M. Prause, Stefan Decker, Oya Beyan, Toralf Kirsten:
Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train. CoRDI 2023 - [c7]Yongli Mou, Jiahang Chen, Zhenghao Zhang, Jürgen Roßmann, Stefan Decker:
Self-sovereign Identity-based Access Control Management in Forestry 4.0. FiCloud 2023: 159-166 - [c6]Yongli Mou, Fengyang Guo, Wei Lu, Yongzhao Li, Oya Beyan, Thomas Rose, Schahram Dustdar, Stefan Decker:
Towards FAIR Data in Distributed Machine Learning Systems. GLOBECOM 2023: 6450-6455 - [c5]Yongli Mou, Jiahui Geng, Feng Zhou, Oya Beyan, Chunming Rong, Stefan Decker:
pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints. PAKDD (2) 2023: 283-294 - [c4]Timo Himmelsbach, Yongli Mou, Stefan Decker, Armin Heinzl:
Towards Federated Machine Learning and Distributed Ledger Technology-based Data Monetization. VLDB Workshops 2023 - [i3]Maximilian Jugl, Sascha Welten, Yongli Mou, Yeliz Ucer Yediel, Oya Deniz Beyan, Ulrich Sax, Toralf Kirsten:
Privacy-Preserving Linkage of Distributed Datasets using the Personal Health Train. CoRR abs/2309.06171 (2023) - 2022
- [c3]Jiahui Geng, Ali Akbar Rehman, Yongli Mou, Stefan Decker, Chunming Rong:
Blockchain-based Cross-organizational Workflow Platform. CloudCom 2022: 53-59 - 2021
- [c2]Yongli Mou, Sascha Welten, Mehrshad Jaberansary, Yeliz Ucer Yediel, Toralf Kirsten, Stefan Decker, Oya Beyan:
Distributed Skin Lesion Analysis Across Decentralised Data Sources. MIE 2021: 352-356 - [c1]Yongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong, Stefan Decker, Oya Beyan:
Optimized Federated Learning on Class-Biased Distributed Data Sources. PKDD/ECML Workshops (1) 2021: 146-158 - [i2]Yongli Mou, Sascha Welten, Yeliz Ucer Yediel, Toralf Kirsten, Oya Deniz Beyan:
Distributed Learning for Melanoma Classification using Personal Health Train. CoRR abs/2103.13226 (2021) - [i1]Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong:
Towards General Deep Leakage in Federated Learning. CoRR abs/2110.09074 (2021)
Coauthor Index
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