Xinyi Xu

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Bryan Kian Hsiang LowAssociate Professor (with tenure), Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Chuan-Sheng FooInstitute for Infocomm Research; A*STAR Centre for Frontier AI ResearchVerified email at cs.stanford.edu
Zhaoxuan WuNational University of SingaporeVerified email at u.nus.edu
Rachael Sim Hwee LingPh.D. candidate, Department of Computer Science, National University of SingaporeVerified email at u.nus.edu
Xiaoqiang LinNational University of SingaporeVerified email at u.nus.edu
See-Kiong NgInstitute of Data Science and School of Computing, National University of SingaporeVerified email at nus.edu.sg
Sebastian Shenghong TayPhD Student, National University of SingaporeVerified email at u.nus.edu
Patrick JailletDugald C. Jackson Professor, EECS, MITVerified email at mit.edu
Zijian ZhouNational University of SingaporeVerified email at u.nus.edu
Arun VermaSingapore-MIT Alliance for Research and TechnologyVerified email at smart.mit.edu
Rui QiaoPhd Student, National University of SingaporeVerified email at u.nus.edu
Yao ShuGuangdong Lab of AI and Digital Economy (SZ)Verified email at gml.ac.cn
Shuaiqi WangCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Giulia FantiCarnegie Mellon University, ECE DepartmentVerified email at andrew.cmu.edu
Wenyang HuNational University of SingaporeVerified email at u.nus.edu
Lam Chi ThanhPh.D. Student, National University of SingaporeVerified email at u.nus.edu
Pang Wei KohUniversity of WashingtonVerified email at cs.washington.edu
Gregory Kang Ruey LauNational University of SingaporeVerified email at comp.nus.edu.sg

Xinyi Xu

Ph.D. student, Department of Computer Science, National University of Singapore

Verified email at u.nus.edu - Homepage

data centric-machine learning federated Learning multi-agent systems cooperative game theory


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Collaborative fairness in federated learning L Lyu, X Xu, Q Wang, H Yu Federated Learning: Privacy and Incentive, 189-204, 2020	209	2020
Gradient driven rewards to guarantee fairness in collaborative machine learning X Xu, L Lyu, X Ma, C Miao, CS Foo, BKH Low Advances in Neural Information Processing Systems 34, 16104-16117, 2021	80	2021
A reputation mechanism is all you need: Collaborative fairness and adversarial robustness in federated learning X Xu, L Lyu Proc. ICML Workshop on Federated Learning for User Privacy and Data …, 2021	76	2021
Validation free and replication robust volume-based data valuation X Xu, Z Wu, CS Foo, BKH Low Advances in Neural Information Processing Systems 34, 10837-10848, 2021	62	2021
Data Valuation in Machine Learning: "Ingredients", Strategies, and Open Challenges RHL Sim, X Xu, BKH Low. 31st International Joint Conference on Artificial Intelligence (IJCAI-22), 2022	45	2022
Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards SS Tay, X Xu, CS Foo, BKH Low 36th AAAI Conference on Artificial Intelligence (AAAI-22), 2022	45	2022
Towards building a robust and fair federated learning system X Xu, L Lyu arXiv preprint arXiv:2011.10464, 2020	41	2020
On the Convergence of the Shapley Value in Parametric Bayesian Learning Games L Agussurja, X Xu, BKH Low 39th International Conference on Machine Learning 162, 180-196, 2022	13	2022
FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery X Xu, Z Wu, A Verma, CS Foo, BKH Low 26th International Conference on Artificial Intelligence and Statistics …, 2023	10	2023
Probably approximate Shapley fairness with applications in machine learning Z Zhou, X Xu, RHL Sim, CS Foo, BKH Low Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5910-5918, 2023	9	2023
Fair yet Asymptotically Equal Collaborative Learning X Lin, X Xu, SK Ng, CS Foo, BKH Low 40th International Conference on Machine Learning (ICML-23), 2023	8	2023
Collaborative causal inference with fair incentives R Qiao, X Xu, BKH Low 40th International Conference on Machine Learning (ICML-23), 2023	6	2023
Hierarchical Reinforcement Learning in StarCraft II with Human Expertise in Subgoals Selection X Xu, T Huang, P Wei, A Narayan, TY Leong Proceedings of the 1st Workshop on Bridging the Gap Between AI Planning and …, 2020	6	2020
Incentives in Private Collaborative Machine Learning RHL Sim, Y Zhang, TN Hoang, X Xu, BKH Low, P Jaillet Advances in Neural Information Processing Systems 36: 37th Annual Conference …, 2023	5	2023
Fairness in federated learning X Lin, X Xu, Z Wu, RHL Sim, SK Ng, CS Foo, P Jaillet, TN Hoang, ... Federated Learning, 143-160, 2024	1	2024
Data valuation in federated learning Z Wu, X Xu, RHL Sim, Y Shu, X Lin, L Agussurja, Z Dai, SK Ng, CS Foo, ... Federated Learning, 281-296, 2024	1	2024
Data-Centric AI in the Age of Large Language Models X Xu, Z Wu, R Qiao, A Verma, Y Shu, J Wang, X Niu, Z He, J Chen, Z Zhou, ... Proceedings of the 2024 Empirical Methods in Natural Language Processing …, 2024		2024
Distributionally Robust Data Valuation X Lin, X Xu, Z Wu, SK Ng, BKH Low Forty-first International Conference on Machine Learning, 2024		2024
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning Z Zhou, X Lin, X Xu, A Prakash, D Rus, BKH Low arXiv preprint arXiv:2405.14899, 2024		2024
Data Distribution Valuation X Xu, S Wang, CS Foo, BKH Low, G Fanti Data-centric Machine Learning Research (DMLR) Workshop at ICLR 2024, 2024		2024

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