Publications
# means equal contribution, $\dagger$ indicates corresponding author
-> Pre-prints
[LLM] LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation [arXiv],
Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Guojun Peng, Zhiguang Cao, Yining Ma $\dagger$, Yue-Jiao Gong $\dagger$.[LLM] Large Language Model with Graph Convolution for Recommendation [arXiv],
Yingpeng Du, Ziyan Wang, Zhu Sun, Haoyan Chua, Hongzhi Liu, Zhonghai Wu, Yining Ma, Jie Zhang, Youchen Sun.
-> Machine Learning for Optimization
# Conference papers
[VRP] MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts,
Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, Jie Zhang, Xu Chi.
International Conference on Machine Learning (ICML), 2024. [Code & Paper][BBO] Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning,
Zeyuan Ma, Jiacheng Chen, Hongshu Guo, Yining Ma, Yue-Jiao Gong.
Genetic and Evolutionary Computation Conference (GECCO), 2024. [Paper][BBO] SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning,
Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong.
International Conference on Learning Representations (ICLR), 2024. [Code & Paper][VRP] Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt,
Yining Ma, Zhiguang Cao, Yeow Meng Chee.
Advances in Neural Information Processing Systems (NeurIPS), pp. 49555-49578, 2023. [Code & Paper][BBO] [Benchmark] MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning,
Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao.
Advances in Neural Information Processing Systems (NeurIPS), Oral, pp. 10775-10795, 2023. [Code & Paper][MOCOP] Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement,
Jinbiao Chen, Zizhen Zhang, Zhiguang Cao, Yaoxin Wu, Yining Ma, Te Ye, Jiahai Wang.
Advances in Neural Information Processing Systems (NeurIPS), pp. 39176-39188, 2023. [Code & Paper][VRP] Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation,
Jieyi Bi#, Yining Ma#, Jiahai Wang, Zhiguang Cao, Jinbiao Chen, Yuan Sun, Yeow Meng Chee.
Advances in Neural Information Processing Systems (NeurIPS), Spotlight, pp. 31226-31238, 2022. [Code & Paper][VRP] Efficient Neural Neighborhood Search for Pickup and Delivery Problems,
Yining Ma#, Jingwen Li#, Zhiguang Cao, Wen Song, Hongliang Guo, Yuejiao Gong, Yeow Meng Chee.
International Joint Conference on Artificial Intelligence (IJCAI), pp. 4776-4784, 2022. [Code & Paper][VRP] Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer,
Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang.
Advances in Neural Information Processing Systems (NeurIPS), pp. 11096-11107, 2021. [Code & Paper]
# Journal papers
[BBO] Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution,
Hongshu Guo, Yining Ma, Zeyuan Ma, Jiacheng Chen, Xinglin Zhang, Zhiguang Cao, Jun Zhang, Yue-Jiao Gong.
IEEE Transactions on Systems, Man and Cybernetics: Systems (SMCA), 2024. [Paper][COP] [Invited Review] A Review on Learning to Solve Combinatorial Optimisation Problems in Manufacturing,
Cong Zhang#, Yaoxin Wu#, Yining Ma#, Wen Song, Le Zhang, Zhiguang Cao, Jie Zhang.
IET Collaborative Intelligent Manufacturing (CIM), vol.5, no.1, pp. e12072, 2023. [Paper][VRP] Learning Feature Embedding Refiner for Solving Vehicle Routing Problems,
Jingwen Li#, Yining Ma#, Zhiguang Cao, Yaoxin Wu, Wen Song, Jie Zhang, Yeow Meng Chee.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. [Code & Paper][VRP] Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem,
Jingwen Li, Yining Ma, Ruize Gao, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang.
IEEE Transactions on Cybernetics (TCYB), vol. 52, no. 12, pp. 13572-13585, 2022. [Code & Paper]
-> Other Topics in Machine Learning
[MARL] Decision-making with Speculative Opponent Models,
Jing Sun, Shuo Chen, Cong Zhang, Yining Ma, Jie Zhang.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. [Paper][Fed] FedHQL: Federated Heterogeneous Q-Learning,
Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Cheston Tan, Bryan Kian Hsiang Low, Roger Wattenhofer.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Extended Abstract, pp. 2810–-2812, 2023. [Paper][Fed] Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee,
Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Kian Hsiang Low.
Advances in Neural Information Processing Systems (NeurIPS), pp. 1007–1021, 2021. [Code & Paper]
-> Other Topics in Optimization
[ACO] MTrajPlanner: A Multiple-Trajectory Planning Algorithm for Autonomous Underwater Vehicles,
Yue-Jiao Gong, Ting Huang, Yining Ma, Sang-Woon Jeon, Jun Zhang.
IEEE Transactions on Intelligent Transportation Systems (TITS), vol. 24, no. 4, pp. 3714-3727, 2023. [Code & Paper][ACO] Path Planning for Autonomous Underwater Vehicles: An Ant Colony Algorithm Incorporating Alarm Pheromone,
Yining Ma, Yue-Jiao Gong, Chu-Feng Xiao, Ying Gao, Jun Zhang.
IEEE Transactions on Vehicular Technology (TVT), vol. 68, no. 1, pp. 141-154, 2019. [Paper][GA] Video Server Deployment Using a Genetic Algorithm with Deterministic Initialization Strategy,
Xin-Yi Hu, Yue-Jiao Gong, Xin-Yuan Zhang, Yining Ma, Jun Zhang.
International Symposium on Neural Networks (ISNN), pp. 459-467, 2018. [Paper]
Patent
- Intelligent video content server deployment method system,
China Invention Grant (No. CN108616401B), 2018. [Link]