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Rachael Hwee Ling Sim
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2020 – today
- 2025
- [i6]Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, Bryan Kian Hsiang Low:
DUPRE: Data Utility Prediction for Efficient Data Valuation. CoRR abs/2502.16152 (2025) - 2024
- [c8]Xiao Tian, Rachael Hwee Ling Sim, Jue Fan, Bryan Kian Hsiang Low:
DeRDaVa: Deletion-Robust Data Valuation for Machine Learning. AAAI 2024: 15373-15381 - [c7]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Position Paper: Data-Centric AI in the Age of Large Language Models. EMNLP (Findings) 2024: 11895-11913 - [c6]Rachael Hwee Ling Sim, Jue Fan, Xiao Tian, Patrick Jaillet, Bryan Kian Hsiang Low:
Deletion-Anticipative Data Selection with a Limited Budget. ICML 2024 - [i5]Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet:
Incentives in Private Collaborative Machine Learning. CoRR abs/2404.01676 (2024) - [i4]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Data-Centric AI in the Age of Large Language Models. CoRR abs/2406.14473 (2024) - 2023
- [c5]Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Probably Approximate Shapley Fairness with Applications in Machine Learning. AAAI 2023: 5910-5918 - [c4]Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet:
Incentives in Private Collaborative Machine Learning. NeurIPS 2023 - [i3]Xiao Tian, Rachael Hwee Ling Sim, Jue Fan, Bryan Kian Hsiang Low:
DeRDaVa: Deletion-Robust Data Valuation for Machine Learning. CoRR abs/2312.11413 (2023) - 2022
- [c3]Rachael Hwee Ling Sim, Xinyi Xu, Bryan Kian Hsiang Low:
Data Valuation in Machine Learning: "Ingredients", Strategies, and Open Challenges. IJCAI 2022: 5607-5614 - [i2]Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low:
Probably Approximate Shapley Fairness with Applications in Machine Learning. CoRR abs/2212.00630 (2022) - 2021
- [c2]Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet:
Collaborative Bayesian Optimization with Fair Regret. ICML 2021: 9691-9701 - 2020
- [c1]Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low:
Collaborative Machine Learning with Incentive-Aware Model Rewards. ICML 2020: 8927-8936 - [i1]Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low:
Collaborative Machine Learning with Incentive-Aware Model Rewards. CoRR abs/2010.12797 (2020)
Coauthor Index
aka: Bryan Kian Hsiang Low
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