Yufei Kuang

According to our database, Yufei Kuang authored at least 22 papers between 2020 and 2025.

Collaborative distances:

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

2025

Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning.

Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu

IEEE Trans. Pattern Anal. Mach. Intell., August, 2025

Advancing Symbolic Discovery on Unsupervised Data: A Pre-training Framework for Non-degenerate Implicit Equation Discovery.

Yufei Kuang, Jie Wang, Huang Haotong, Mingxuan Ye, Fangzhou Zhu, Xijun Li, Jianye Hao, Wu Feng

CoRR, May, 2025

Long-Term Feature Extraction via Frequency Prediction for Efficient Reinforcement Learning.

Jie Wang, Mingxuan Ye, Yufei Kuang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu

IEEE Trans. Pattern Anal. Mach. Intell., April, 2025

A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization.

Yinqi Bai, Jie Wang, Lei Chen, Zhihai Wang, Yufei Kuang, Mingxuan Yuan, Jianye Hao, Feng Wu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming.

Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition.

Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu

CoRR, 2024

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming.

Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu

CoRR, 2024

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications.

Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao

CoRR, 2024

Neural Krylov Iteration for Accelerating Linear System Solving.

Jian Luo, Jie Wang, Hong Wang, Huanshuo Dong, Zijie Geng, Hanzhu Chen, Yufei Kuang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition.

Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space.

Qianmei Liu, Yufei Kuang, Jie Wang

Proceedings of the International Joint Conference on Neural Networks, 2024

Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph.

Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu

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

Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework.

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics.

Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

State Sequences Prediction via Fourier Transform for Representation Learning.

Mingxuan Ye, Yufei Kuang, Jie Wang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu

CoRR, 2023

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation.

Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu

CoRR, 2023

Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning.

Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu

CoRR, 2023

Learning robust representation for reinforcement learning with distractions by reward sequence prediction.

Qi Zhou, Jie Wang, Qiyuan Liu, Yufei Kuang, Wengang Zhou, Houqiang Li

Proceedings of the Uncertainty in Artificial Intelligence, 2023

State Sequences Prediction via Fourier Transform for Representation Learning.

Mingxuan Ye, Yufei Kuang, Jie Wang, Yang Rui, Wengang Zhou, Houqiang Li, Feng Wu

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

Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model.

Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization.

Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020

Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method.

Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020