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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. |
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Preprints(*: equal contribution, __: student first author I co-mentor) |
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Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang pdf / arXiv |
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Instance-Conditioned Adaptation for Large-scale Generalization of Neural Combinatorial Optimization
Changliang Zhou*, Xi Lin*, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang pdf / arXiv |
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Self-Improved Learning for Scalable Neural Combinatorial Optimization
Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang pdf / arXiv |
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PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang pdf / arXiv |
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Large Language Model for Multi-objective Evolutionary Optimization
Fei Liu, Xi Lin, Zhenkun Wang, Shunyu Yao, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang pdf / arXiv |
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Multi-Objective Evolution of Heuristic Using Large Language Model
Shunyu Yao*, Fei Liu*, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang pdf / arXiv |
Survey and Package(*: equal contribution, __: student first author I co-mentor) |
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A Systematic Survey on Large Language Models for Algorithm Design (New)
Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang pdf / arXiv |
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LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch (New)
Xiaoyuan Zhang*, Liang Zhao*, Yingying Yu*, Xi Lin, Zhenkun Wang, Han Zhao, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2024 pdf / arXiv / code |
Selected Publications(*: equal contribution, __: student first author I co-mentor, full list: Google Scholar) |
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Dealing with Structure Constraints in Evolutionary Pareto Set Learning
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang IEEE Transactions on Evolutionary Computation, to appear pdf / arXiv |
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Gliding over the Pareto Front with Uniform Designs
Xiaoyuan Zhang, Genghui Li, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2024 pdf / arXiv |
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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 / openreview / code |
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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 (Oral Presentation, Top 1.6% among All Submissions) pdf / arXiv / openreview / code |
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Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Models
Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang International Conference on Parallel Problem Solving From Nature (PPSN), 2024 pdf / arXiv / code |
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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 / code |
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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 |
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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 |
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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 |
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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 |
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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 |
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Controllable Pareto Multi-Task Learning
Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong Technical Report, 2020 pdf / arXiv |
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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): Transactions on Machine Learning Research (TMLR) |
| Conference Reviewer: ICML, ICLR, NeurIPS, AISTATS, GECCO, CEC, SSCI |
| Journal Reviewer: JMLR, TMLR, TEVC, TCYB, TNNLS, TAI, TETCI, NN, SWEVO, COR |
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Awards:
Expert Reviewer, TMLR 2023 Outstanding Reviewer, ICML 2021, ICML 2022 Highlighted Reviewer, ICLR 2022 |
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This website's source code is adapted from Jon Barron's public academic website. |