Provably Near-Optimal Balancing Policies for Multi-Echelon Stochastic Inventory Control Models. - Retsef Levi; Robin Roundy; Van-Anh Truong; Xinshang Wang (Math. Oper. Res., 2017)

The Lingering of Gradients: How to Reuse Gradients Over Time. - Zeyuan Allen-Zhu; David Simchi-Levi; Xinshang Wang (NeurIPS, 2018)

Multi-Priority Online Scheduling with Cancellations. - Xinshang Wang; Van-Anh Truong (Oper. Res., 2018)

Conservative Exploration for Semi-Bandits with Linear Generalization: A Product Selection Problem for Urban Warehouses. - Rong Jin 001; David Simchi-Levi; Li Wang 082; Xinshang Wang; Sen Yang (CoRR, 2019)

Approximation Algorithms for Product Framing and Pricing. - Guillermo Gallego 001; Anran Li 002; Van-Anh Truong; Xinshang Wang (Oper. Res., 2020)

Advance Service Reservations with Heterogeneous Customers. - Clifford Stein 001; Van-Anh Truong; Xinshang Wang (Manag. Sci., 2020)

A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments. - Yu-Hang Zhou; Peng Hu; Chen Liang; Huan Xu; Guangda Huzhang; Yinfu Feng; Qing Da; Xinshang Wang; Anxiang Zeng (AAAI, 2021)

Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses. - Rong Jin 001; David Simchi-Levi; Li Wang 082; Xinshang Wang; Sen Yang (Manag. Sci., 2021)

On Representing Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Jianfeng Lu 001; Wotao Yin (CoRR, 2022)

On Representing Mixed-Integer Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Jianfeng Lu 001; Wotao Yin (CoRR, 2022)

Inventory Balancing with Online Learning. - Wang Chi Cheung; Will Ma; David Simchi-Levi; Xinshang Wang (Manag. Sci., 2022)

HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent. - Ziang Chen; Jianfeng Lu 001; Huajie Qian; Xinshang Wang; Wotao Yin (AISTATS, 2023)

On Representing Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (ICLR, 2023)

On Representing Mixed-Integer Linear Programs by Graph Neural Networks. - Ziang Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (ICLR, 2023)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Wang 004; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (CoRR, 2023)

Efficient Algorithms for Sum-Of-Minimum Optimization. - Lisang Ding; Ziang Chen; Xinshang Wang; Wotao Yin (ICML, 2024)

Rethinking the Capacity of Graph Neural Networks for Branching Strategy. - Ziang Chen; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Wotao Yin (NeurIPS, 2024)

Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs. - Ziang Chen; Xiaohan Chen; Jialin Liu 003; Xinshang Wang; Wotao Yin (CoRR, 2024)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Peter Wang; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (Trans. Mach. Learn. Res., 2024)

DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models. - Zeping Min; Xinshang Wang (ICLR, 2025)

Technical Note - Online Matching with Bayesian Rewards. - David Simchi-Levi; Rui Sun; Xinshang Wang (Oper. Res., 2025)

Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints. - Ruicheng Ao; Gan Luo; David Simchi-Levi; Xinshang Wang (CoRR, 2025)