Xi Lin

According to our database, Xi Lin authored at least 38 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Decomposition gradient descent method for bi-objective optimisation.

Jingjing Chen, Genghui Li, Xi Lin

Int. J. Bio Inspired Comput., 2024

A Systematic Survey on Large Language Models for Algorithm Design.

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang

CoRR, 2024

Multi-objective Evolution of Heuristic Using Large Language Model.

Shunyu Yao, Fei Liu, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang

CoRR, 2024

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch.

Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Zhenkun Wang, Han Zhao, Qingfu Zhang

CoRR, 2024

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization.

Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang

CoRR, 2024

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Combinatorial Optimization.

Changliang Zhou, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Self-Improved Learning for Scalable Neural Combinatorial Optimization.

Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume.

Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang

CoRR, 2024

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.

Fei Liu, Xi Lin, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

CoRR, 2024

PMGDA: A Preference-based Multiple Gradient Descent Algorithm.

Xiaoyuan Zhang, Xi Lin, Qingfu Zhang

CoRR, 2024

UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition.

Xiaoyuan Zhang, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang

CoRR, 2024

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks.

Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang

CoRR, 2024

PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks.

Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang

CoRR, 2024

An Example of Evolutionary Computation + Large Language Model Beating Human: Design of Efficient Guided Local Search.

Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang

CoRR, 2024

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

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Many-Objective Cover Problem: Discovering Few Solutions to Cover Many Objectives.

Yilu Liu, Chengyu Lu, Xi Lin, Qingfu Zhang

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.

Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Prompt Learning for Generalized Vehicle Routing.

Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Smooth Tchebycheff Scalarization for Multi-Objective Optimization.

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

L-AutoDA: Large Language Models for Automatically Evolving Decision-based Adversarial Attacks.

Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

Evolutionary Pareto Set Learning with Structure Constraints.

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang

CoRR, 2023

Large Language Model for Multi-objective Evolutionary Optimization.

Fei Liu, Xi Lin, Zhenkun Wang, Shunyu Yao, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2023

Hypervolume Maximization: A Geometric View of Pareto Set Learning.

Xiaoyuan Zhang, Xi Lin, Bo Xue, Yifan Chen, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization.

Fu Luo, Xi Lin, Fei Liu, Qingfu Zhang, Zhenkun Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continuation Path Learning for Homotopy Optimization.

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Proceedings of the International Conference on Machine Learning, 2023

Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables.

Ping Guo, Qingfu Zhang, Xi Lin

Proceedings of the Evolutionary Multi-Criterion Optimization, 2023

2022

Pareto Set Learning for Expensive Multi-Objective Optimization.

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization.

Xi Lin, Zhiyuan Yang, Qingfu Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Images.

Jianfei Guo, Zhiyuan Yang, Xi Lin, Qingfu Zhang

CoRR, 2021

2020

Fast Covariance Matrix Adaptation for Large-Scale Black-Box Optimization.

Zhenhua Li, Qingfu Zhang, Xi Lin, Hui-Ling Zhen

IEEE Trans. Cybern., 2020

Evolution strategies for continuous optimization: A survey of the state-of-the-art.

Zhenhua Li, Xi Lin, Qingfu Zhang, Hai-Lin Liu

Swarm Evol. Comput., 2020

Controllable Pareto Multi-Task Learning.

Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong

CoRR, 2020

2019

Pareto Multi-Task Learning.

Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Batched Scalable Multi-Objective Bayesian Optimization Algorithm.

Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong

CoRR, 2018

Nonlinear Collaborative Scheme for Deep Neural Networks.

Hui-Ling Zhen, Xi Lin, Alan Z. Tang, Zhenhua Li, Qingfu Zhang, Sam Kwong

CoRR, 2018

2017

An efficient batch expensive multi-objective evolutionary algorithm based on Decomposition.

Xi Lin, Qingfu Zhang, Sam Kwong

Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016

A decomposition based multiobjective evolutionary algorithm with classification.

Xi Lin, Qingfu Zhang, Sam Kwong

Proceedings of the IEEE Congress on Evolutionary Computation, 2016