A First Look at Information Entropy-Based Data Pricing. - Xijun Li; Jianguo Yao; Xue Liu 001; Haibing Guan (ICDCS, 2017)

A Two-Layer Algorithmic Framework for Service Provider Configuration and Planning with Optimal Spatial Matching. - Xijun Li; Jianguo Yao; Mingxuan Yuan; Jia Zeng (CIKM, 2018)

A Data-Driven Three-Layer Algorithm for Split Delivery Vehicle Routing Problem with 3D Container Loading Constraint. - Xijun Li; Mingxuan Yuan; Di Chen; Jianguo Yao; Jia Zeng (KDD, 2018)

Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. - Xijun Li; Weilin Luo; Mingxuan Yuan; Jun Wang 012; Jiawen Lu; Jie Wang 005; Jinhu Lü; Jia Zeng (ICDE, 2021)

Learning-Aided Heuristics Design for Storage System. - Yingtian Tang; Han Lu; Xijun Li; Lei Chen 031; Mingxuan Yuan; Jia Zeng (SIGMOD Conference, 2021)

Learning to Optimize DAG Scheduling in Heterogeneous Environment. - Jinhong Luo; Xijun Li; Mingxuan Yuan; Jianguo Yao; Jia Zeng (CoRR, 2021)

L-QoCo: learning to optimize cache capacity overloading in storage systems. - Ji Zhang; Xijun Li; Xiyao Zhou; Mingxuan Yuan; Zhuo Cheng; Keji Huang; Yifan Li (DAC, 2022)

Learning to Optimize DAG Scheduling in Heterogeneous Environment. - Yunfan Zhou; Xijun Li; Jinhong Luo; Mingxuan Yuan; Jia Zeng; Jianguo Yao (MDM, 2022)

An Improved Reinforcement Learning Algorithm for Learning to Branch. - Qingyu Qu; Xijun Li; Yunfan Zhou; Jia Zeng; Mingxuan Yuan; Jie Wang 005; Jinhu Lv; Kexin Liu; Kun Mao 001 (CoRR, 2022)

Learning to Reformulate for Linear Programming. - Xijun Li; Qingyu Qu; Fangzhou Zhu; Jia Zeng; Mingxuan Yuan; Kun Mao 001; Jie Wang 005 (CoRR, 2022)

Introduction to The Dynamic Pickup and Delivery Problem Benchmark - ICAPS 2021 Competition. - Jianye Hao; Jiawen Lu; Xijun Li; Xialiang Tong; Xiang Xiang 001; Mingxuan Yuan; Hankz Hankui Zhuo (CoRR, 2022)

Yordle: An Efficient Imitation Learning for Branch and Bound. - Qingyu Qu; Xijun Li; Yunfan Zhou (CoRR, 2022)

A Survey for Solving Mixed Integer Programming via Machine Learning. - Jiayi Zhang 003; Chang Liu 021; Junchi Yan; Xijun Li; Hui-Ling Zhen; Mingxuan Yuan (CoRR, 2022)

Machine Learning Methods in Solving the Boolean Satisfiability Problem. - Wenxuan Guo; Junchi Yan; Hui-Ling Zhen; Xijun Li; Mingxuan Yuan; Yaohui Jin (CoRR, 2022)

LQoCo: Learning to Optimize Cache Capacity Overloading in Storage Systems. - Ji Zhang; Xijun Li; Xiyao Zhou; Mingxuan Yuan; Zhuo Cheng; Keji Huang; Yifan Li (CoRR, 2022)

Offline Reinforcement Learning with Adaptive Behavior Regularization. - Yunfan Zhou; Xijun Li; Qingyu Qu (CoRR, 2022)

Multiobjective Optimization-Aided Decision-Making System for Large-Scale Manufacturing Planning. - Zhenkun Wang 001; Hui-Ling Zhen; Jingda Deng; Qingfu Zhang 001; Xijun Li; Mingxuan Yuan; Jia Zeng (IEEE Trans. Cybern., 2022)

ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs. - Han Lu; Zenan Li; Runzhong Wang; Qibing Ren; Xijun Li; Mingxuan Yuan; Jia Zeng; Xiaokang Yang 001; Junchi Yan (ICLR, 2023)

Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. - Zhihai Wang; Xijun Li; Jie Wang 005; Yufei Kuang; Mingxuan Yuan; Jia Zeng; Yongdong Zhang 001; Feng Wu 001 (ICLR, 2023)

SGDP: A Stream-Graph Neural Network Based Data Prefetcher. - Yiyuan Yang; Rongshang Li; Qiquan Shi; Xijun Li; Gang Hu; Xing Li; Mingxuan Yuan (IJCNN, 2023)

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline. - Yang Li 197; Xinyan Chen; Wenxuan Guo; Xijun Li; Wanqian Luo; Junhua Huang; Hui-Ling Zhen; Mingxuan Yuan; Junchi Yan (KDD, 2023)

A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability. - Zijie Geng; Xijun Li; Jie Wang 005; Xiao Li; Yongdong Zhang 001; Feng Wu 001 (NeurIPS, 2023)

Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. - Yufei Kuang; Xijun Li; Jie Wang 005; Fangzhou Zhu; Meng Lu; Zhihai Wang; Jia Zeng; Houqiang Li; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2023)

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. - Haoyang Liu 002; Yufei Kuang; Jie Wang 005; Xijun Li; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2023)

A survey for solving mixed integer programming via machine learning. - Jiayi Zhang 003; Chang Liu 021; Xijun Li; Hui-Ling Zhen; Mingxuan Yuan; Yawen Li 001; Junchi Yan (Neurocomputing, 2023)

Satellite Observation and Data-Transmission Scheduling Using Imitation Learning Based on Mixed Integer Linear Programming. - Qingyu Qu; Kexin Liu; Xijun Li; Yunfan Zhou; Jinhu Lü (IEEE Trans. Aerosp. Electron. Syst., 2023)

Machine Learning Methods in Solving the Boolean Satisfiability Problem. - Wenxuan Guo; Hui-Ling Zhen; Xijun Li; Wanqian Luo; Mingxuan Yuan; Yaohui Jin; Junchi Yan (Mach. Intell. Res., 2023)

Joint Directory, File and IO Trace Feature Extraction and Feature-based Trace Regeneration for Enterprise Storage Systems. - Kecheng Huang; Xijun Li; Mingxuan Yuan; Ji Zhang; Zili Shao (ICDE, 2024)

Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework. - Yufei Kuang; Jie Wang 005; Haoyang Liu 002; Fangzhou Zhu; Xijun Li; Jia Zeng; Jianye Hao; Bin Li 025; Feng Wu 001 (ICLR, 2024)

L2P-MIP: Learning to Presolve for Mixed Integer Programming. - Chang Liu 021; Zhichen Dong; Haobo Ma; Weilin Luo; Xijun Li; Bowen Pang; Jia Zeng; Junchi Yan (ICLR, 2024)

Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph. - Yufei Kuang; Jie Wang 005; Yuyan Zhou; Xijun Li; Fangzhou Zhu; Jianye Hao; Feng Wu 001 (ICML, 2024)

A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design. - Zhihai Wang; Lei Chen 031; Jie Wang 005; Yinqi Bai; Xing Li; Xijun Li; Mingxuan Yuan; Jianye Hao; Yongdong Zhang 001; Feng Wu 001 (ICML, 2024)

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. - Haoyang Liu 002; Jie Wang 005; Wanbo Zhang; Zijie Geng; Yufei Kuang; Xijun Li; Bin Li 025; Yongdong Zhang 001; Feng Wu 005 (NeurIPS, 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 197; et al. (CoRR, 2024)

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. - Jie Wang 005; Zhihai Wang; Xijun Li; Yufei Kuang; Zhihao Shi; Fangzhou Zhu; Mingxuan Yuan; Jia Zeng; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2024)

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. - Haoyang Liu 002; Jie Wang 005; Wanbo Zhang; Zijie Geng; Yufei Kuang; Xijun Li; Bin Li 025; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2024)

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. - Jie Wang 005; Zhihai Wang; Xijun Li; Yufei Kuang; Zhihao Shi; Fangzhou Zhu; Mingxuan Yuan; Jia Zeng; Yongdong Zhang 001; Feng Wu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming. - Haoyang Liu 002; Jie Wang 005; Zijie Geng; Xijun Li; Yuxuan Zong; Fangzhou Zhu; Jianye Hao; Feng Wu 001 (ICLR, 2025)

Differentiable Integer Linear Programming. - Zijie Geng; Jie Wang 005; Xijun Li; Fangzhou Zhu; Jianye Hao; Bin Li 025; Feng Wu 001 (ICLR, 2025)

A repulsive-distance-based maximum diversity selection algorithm for multimodal multiobjective optimization. - Qi Deng; Yuan Liu 026; Shengxiang Yang; Juan Zou; Xijun Li; Yizhang Xia; Jinhua Zheng (Appl. Soft Comput., 2025)

Layout Decomposition via Boolean Satisfiability. - Hongduo Liu; Peiyu Liao; Mengchuan Zou; Bowen Pang; Xijun Li; Mingxuan Yuan; Tsung-Yi Ho; Bei Yu 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

Advancing Symbolic Discovery on Unsupervised Data: A Pre-training Framework for Non-degenerate Implicit Equation Discovery. - Yufei Kuang; Jie Wang 005; Huang Haotong; Mingxuan Ye; Fangzhou Zhu; Xijun Li; Jianye Hao; Wu Feng (CoRR, 2025)

STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization. - Xijun Li; Jiexiang Yang; Jinghao Wang; Bo Peng; Jianguo Yao; Haibing Guan (CoRR, 2025)

Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. - Yufei Kuang; Xijun Li; Jie Wang 005; Fangzhou Zhu; Meng Lu; Zhihai Wang; Jia Zeng; Houqiang Li; Yongdong Zhang 001; Feng Wu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)