Lin Xiaoqiang

I am a third-year PhD student from National University of Singapore, advised by Assoc. Prof. Bryan Low and Prof. See-Kiong Ng. Before that, I was a full time machine learning engineer at Ant Group. I received my Bachelor's degree from the Fudan University, where I worked with Assoc. Prof. Zhongyu Wei.

Recent Updates

[2 May 2024] My 3 papers are accepted by ICML 2024!

[5 Oct 2023] Our instruction optimization paper (INSTINCT) is avaliable on arxiv now.

[10 Aug 2023] I receive Research Achievement Award from NUS School of Computing.

[8 Aug 2023] Our paper "Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients" is avaliable on arxiv now.

[24 Apr 2023] Our paper "Fair yet Asymptotically Equal Collaborative Learning" is accepted by ICML 2023.

Research Interests

Data-centric AI for large models (e.g., data selection/curation in different stages of training for large models and use of data at inference).

Collaborative machine learning (e.g., federated learning, incentive mechanism).

Data valuation (e.g., data pricing, data subset selection, data debugging).

Gaussian process and its applications (e.g., zeroth-order optimization, Bayesian optimization).

Publications

Distributionally Robust Data Valuation.
Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, See-Kiong Ng, Bryan Kian Hsiang Low.
International Conference on Machine Learning (ICML), 2024.
Paper

Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers.
Xiaoqiang Lin*, Zhaoxuan Wu*, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low.
International Conference on Machine Learning (ICML), 2024.
Project Page / Paper / Code / Bibtex

Robust and Fine-tuning-free Instance Attribution for Interpretable NLP.
Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low.
International Conference on Machine Learning (ICML), 2024.
Paper

Fair yet Asymptotically Equal Collaborative Learning.
Xiaoqiang Lin*, Xinyi Xu*, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low.
International Conference on Machine Learning (ICML), 2023.
Paper / Code / Bibtex

Joint Representation Learning of Legislator and Legislation for Roll Call Prediction.
Yuqiao Yang*, Xiaoqiang Lin*, Geng Lin, Zengfeng Huang, Changjian Jiang, Zhongyu Wei.
International Joint Conferences on Artificial Intelligence (IJCAI), 2020.
Paper / Code / Bibtex

(* denotes equal contribution)

Book Chapters

Fairness in Federated Learning.
Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, Rachael Hwee Ling Sim, See-Kiong Ng, Chuan-Sheng Foo, Patrick Jaillet, Trong Nghia Hoang, and Bryan Kian Hsiang Low.
In L. M. Nguyen, T. N. Hoang, P.-Y. Chen, editors, Federated Learning: Theory and Practice, chapter 8, pages 143-160, Academic Press, 2024.

Data Valuation in Federated Learning.
Zhaoxuan Wu, Xinyi Xu, Rachael Hwee Ling Sim, Yao Shu, Xiaoqiang Lin, Lucas Agussurja, Zhongxiang Dai, See-Kiong Ng, Chuan-Sheng Foo, Patrick Jaillet, Trong Nghia Hoang, Bryan Kian Hsiang Low.
In L. M. Nguyen, T. N. Hoang, P.-Y. Chen, editors, Federated Learning: Theory and Practice, chapter 8, pages 143-160, Academic Press, 2024.

Incentives in Federated Learning.
Rachael Hwee Ling Sim, Sebastian Shenghong Tay, Xinyi Xu, Yehong Zhang, Zhaoxuan Wu, Xiaoqiang Lin, See-Kiong Ng, Chuan-Sheng Foo, Patrick Jaillet, Trong Nghia Hoang, Bryan Kian Hsiang Low.
In L. M. Nguyen, T. N. Hoang, P.-Y. Chen, editors, Federated Learning: Theory and Practice, chapter 8, pages 143-160, Academic Press, 2024.

Pre-Prints

Localized Zeroth-Order Prompt Optimization.
Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiangqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low.
Pre-print, 2024. [arXiv]
Paper

Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients.
Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low.
Pre-print, 2023. [arXiv]
Paper / Bibtex

Invited Talks

Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers.
@ Deep Learning and Optimization Seminar (Jointly organized by Westlake University, City University of Hong Kong, Peking University). Oct 24, 2023. Video

Awards and Honors

Award of Teaching Fellowship, National University of Singapore, 2023 (1 of 3 selected CS Ph.D. students).
Research Achievement Award, NUS, School of Computing, 2023.
Outstanding Graduates, Fudan University, 2020.
Excellent Student Scholarship, Fudan University, 2017, 2018, 2019.

Professional Services

Conference Reviewer for ICML’2024.
Conference Reviewer for AISTATS’2024.
Conference Reviewer for AAAI’2024.
Conference Reviewer for ACML’2023.
Conference Reviewer for ICML’2021.

Contact

You are very welcome to contact me regarding my research. I typically respond within a few days.
I can be contacted directly at xiaoqiang.lin [at] u.nus.edu