NUS - Institute of Data Science

The following is a list of publications from the project team, most of which are in the top 10% of S&T journals and conferences in the field as tracked in a list approved by NRF and/or in the Clarivate Analytics Journal Citation Reports.

Conference Publications

Accepted for 38th IEEE International Conference on Data Engineering (ICDE-2022)

Qinlin Li, Yiqun Diao, Quan Chen, Bingsheng He

Link: https://arxiv.org/abs/2102.02079

Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Vancouver, BC, Canada, 22 Feb - 1 Mar 2022

Joel Q. L. Chang, Vincent Y. F. Tan

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Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Vancouver, BC, Canada, 22 Feb - 1 Mar 2022

Sebastian Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low

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In Proceedings of Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS-2021), 6 - 14 Dec 2021

Xinyi Xu, Zhaoxuan Wu, Chuan-Sheng Foo & Bryan Kian Hsiang Low

Link: https://proceedings.neurips.cc/paper/2021/hash/59a3adea76fadcb6dd9e54c96fc155d1-Abstract.html

In Proceedings of Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS-2021), 6 - 14 Dec 2021

Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Link https://proceedings.neurips.cc/paper/2021/hash/8682cc30db9c025ecd3fee433f8ab54c-Abstract.html

To appear in 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 21-26 August 2021.

Qinbin Li, Bingsheng He, Dawn Song

Link: https://www.ijcai.org/proceedings/2021/205

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Survey Track. Pages 4661-4668.

Zeyi Wen, Qinbin Li, Bingsheng He , Bin Cui

Link: https://www.ijcai.org/proceedings/2021/632

Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI-21), Jul 27-30, 2021.

Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet

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Proceedings of the 38th International Conference on Machine Learning (ICML-2021), 18-24 July 2021

Zixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan

Link: https://icml.cc/virtual/2021/poster/10685

Proceedings of the 38th International Conference on Machine Learning (ICML-2021), 18-24 July 2021

Rachael Hwee Ling Sim, Yehong Zhang, Kian Hsiang Low & Patrick Jaillet

Link: https://icml.cc/Conferences/2021/ScheduleMultitrack?event=9460

Proceedings of the 38th International Conference on Machine Learning (ICML-21), pages 5948-5958, Jul 18-24, 2021.

Chi Thanh Lam, Trong Nghia Hoang, Kian Hsiang Low & Patrick Jaillet.

Link: http://proceedings.mlr.press/v139/lam21a.html

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 19-25 2021, pp. 10713-10722

Qinbin Li, Bingsheng He, Dawn Song

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Journals

IEEE Transactions on Knowledge and Data Engineering (TKDE)

Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He

Link: https://arxiv.org/abs/1907.09693

Accepted and to be published in Journal of Machine Learning Research 2021.

Zixin Zhong, Wang Chi Cheung, and Vincent Y. F. Tan

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Other Publications

Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

Yizhou Chen, Shizhuo Zhang, Bryan Kian Hsiang Low.

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Accepted for IEEE Transactions on Big Data

Zhaomin Wu, Qinbin Li, Bingsheng He.

Link: https://ieeexplore-ieee-org.libproxy1.nus.edu.sg/abstract/document/9789268

Under Review

Book chapter in "Federated Learning: Theory and Practice", to be published by Elsevier

Warren Chik, Florian Gamper

Publications (SG)

Conference Publications

Federated Learning on Non-IID Data Silos: An Experimental Study

A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits

Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards

Validation Free and Replication Robust Volume-based Data Valuation

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning

Practical One-Shot Federated Learning for Cross-Silo Setting

Challenges and Opportunities of Building Fast GBDT Systems

Learning to Learn with Gaussian Processes

Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with Corruptions

Collaborative Bayesian Optimization with Fair Regret

Model Fusion for Personalized Learning

Model-Contrastive Federated Learning

Journals

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection

Thompson Sampling Algorithms for Cascading Bandits

Other Publications

Near-Optimal Task Selection with Mutual Information for Meta-Learning

Practical Vertical Federated Learning with Unsupervised Representation Learning

Under Review

Ethical considerations and legal issues relating to Federated Learning