Xi Lin (林熙)

Xi Lin is currently a Post Doctoral Research Fellow with Department of Computer Science at the City University of Hong Kong, working with Prof. Qingfu Zhang. He received the B.Sc. degree from South China University of Technology, the M.A. degree from Columbia University, and the Ph.D. degree from City University of Hong Kong under the supervision of Prof. Qingfu Zhang and Prof. Sam Kwong.

His research interests include multi-objective optimization, learning based optimization, Bayesian optimization, evolutionary computation and multi-task learning. His work has been published in top-tier machine learning conferences such as ICML, NeurIPS and ICLR. He serves as an Action Editor for Transactions on Machine Learning Research (TMLR). He is a regular reviewer for many machine learning and evolutionary computation conferences and journals, and has received several outstanding reviewer awards from ICML, ICLR and TMLR.

Email  /  Google Scholar  /  Github

profile photo

Selected Publications

(*: equal contribution, __: student first author I co-mentor)
Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang
International Conference on Machine Learning (ICML), 2024
pdf / arXiv
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
International Conference on Machine Learning (ICML), 2024
pdf / arXiv
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
pdf / arXiv
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
Fu Luo*, Xi Lin*, Fei Liu, Qingfu Zhang, Zhenkun Wang
Advances in Neural Information Processing Systems (NeurIPS) , 2023
pdf / arXiv / openreview / code
Hypervolume Maximization: A Geometric View of Pareto Set Learning
Xiaoyuan Zhang, Xi Lin, Bo Xue, Yifan Chen, Qingfu Zhang
Advances in Neural Information Processing Systems (NeurIPS) , 2023
pdf / openreview
Continuation Path Learning for Homotopy Optimization
Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang
International Conference on Machine Learning (ICML), 2023 (Oral Presentation, Top 2.4% among All Submissions)
pdf / arXiv / openreview / code
Pareto Set Learning for Expensive Multi-Objective Optimization
Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang
Advances in Neural Information Processing Systems (NeurIPS) , 2022
pdf / arXiv / openreview / code
Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization
Xi Lin, Zhiyuan Yang, Qingfu Zhang
International Conference on Learning Representations (ICLR) , 2022
pdf / arXiv / openreview / code
Controllable Pareto Multi-Task Learning
Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong
Technical Report, 2020
pdf / arXiv
Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong
Advances in Neural Information Processing Systems (NeurIPS) , 2019
pdf / arXiv / proceedings / code

Academic Service

Action Editor (aka Associate Editor): TMLR
Conference Reviewer: ICML, ICLR, NeurIPS, AISTATS, GECCO, CEC, SSCI
Journal Reviewer: JMLR, TMLR, TEVC, TCYB, TNNLS, TAI, TETCI, SWEVO, COR
Awards:
Expert Reviewer, TMLR 2023
Outstanding Reviewer, ICML 2021, ICML 2022
Highlighted Reviewer, ICLR 2022

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