| Pareto multi-task learning X Lin, HL Zhen, Z Li, Q Zhang, S Kwong 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019 | 309 | 2019 |
| Controllable pareto multi-task learning X Lin, Z Yang, Q Zhang, S Kwong arXiv preprint arXiv:2010.06313, 2020 | 62 | 2020 |
| Evolution strategies for continuous optimization: A survey of the state-of-the-art Z Li, X Lin, Q Zhang, H Liu Swarm and Evolutionary Computation 56, 100694, 2020 | 62 | 2020 |
| Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization X Lin, Z Yang, Q Zhang 10th International Conference on Learning Representations (ICLR 2022), 2022 | 61 | 2022 |
| Fast covariance matrix adaptation for large-scale black-box optimization Z Li, Q Zhang, X Lin, HL Zhen IEEE transactions on cybernetics 50 (5), 2073-2083, 2018 | 47 | 2018 |
| Pareto Set Learning for Expensive Multi-Objective Optimization X Lin, Z Yang, X Zhang, Q Zhang 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022 | 36 | 2022 |
| A decomposition based multiobjective evolutionary algorithm with classification X Lin, Q Zhang, S Kwong 2016 IEEE congress on evolutionary computation (CEC), 3292-3299, 2016 | 36 | 2016 |
| Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization F Luo*, X Lin*, F Liu, Q Zhang, Z Wang 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023 | 25 | 2023 |
| Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model F Liu, X Tong, M Yuan, X Lin, F Luo, Z Wang, Z Lu, Q Zhang 41st International Conference on Machine Learning (ICML 2024), 2024 | 18* | 2024 |
| Large language model for multi-objective evolutionary optimization F Liu, X Lin, Z Wang, S Yao, X Tong, M Yuan, Q Zhang arXiv preprint arXiv:2310.12541, 2023 | 17 | 2023 |
| A batched scalable multi-objective bayesian optimization algorithm X Lin, HL Zhen, Z Li, Q Zhang, S Kwong arXiv preprint arXiv:1811.01323, 2018 | 13 | 2018 |
| An efficient batch expensive multi-objective evolutionary algorithm based on decomposition X Lin, Q Zhang, S Kwong 2017 IEEE Congress on Evolutionary Computation (CEC), 1343-1349, 2017 | 11 | 2017 |
| Template nerf: Towards modeling dense shape correspondences from category-specific object images J Guo, Z Yang, X Lin, Q Zhang arXiv preprint arXiv:2111.04237, 2021 | 7 | 2021 |
| Hypervolume Maximization: A Geometric View of Pareto Set Learning X Zhang, X Lin, B Xue, Y Chen, Q Zhang 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023 | 6 | 2023 |
| Nonlinear collaborative scheme for deep neural networks HL Zhen, X Lin, AZ Tang, Z Li, Q Zhang, S Kwong arXiv preprint arXiv:1811.01316, 2018 | 6 | 2018 |
| Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization F Liu, X Lin, Q Zhang, X Tong, M Yuan 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024 | 4 | 2024 |
| Puridefense: Randomized local implicit adversarial purification for defending black-box query-based attacks P Guo, Z Yang, X Lin, Q Zhao, Q Zhang arXiv preprint arXiv:2401.10586, 2024 | 3 | 2024 |
| Self-Improved Learning for Scalable Neural Combinatorial Optimization F Luo, X Lin, Z Wang, T Xialiang, M Yuan, Q Zhang arXiv preprint arXiv:2403.19561, 2024 | 2 | 2024 |
| L-autoda: Leveraging large language models for automated decision-based adversarial attacks P Guo, F Liu, X Lin, Q Zhao, Q Zhang arXiv preprint arXiv:2401.15335, 2024 | 2 | 2024 |
| Continuation Path Learning for Homotopy Optimization X Lin, Z Yang, X Zhang, Q Zhang 40th International Conference on Machine Learning (ICML 2023), 2023 | 2 | 2023 |
Qingfu ZhangChair Professor, FIEEE, City University of Hong KongVerified email at cityu.edu.hk