Online Stochastic Optimization with Wasserstein Based Non-stationarity. - Jiashuo Jiang; Xiaocheng Li; Jiawei Zhang 006 (CoRR, 2020)

Non-stationary Bandits with Knapsacks. - Shang Liu; Jiashuo Jiang; Xiaocheng Li (NeurIPS, 2022)

Tight Guarantees for Multi-unit Prophet Inequalities and Online Stochastic Knapsack. - Jiashuo Jiang; Will Ma; Jiawei Zhang 006 (SODA, 2022)

Degeneracy is OK: Logarithmic Regret for Network Revenue Management with Indiscrete Distributions. - Jiashuo Jiang; Will Ma; Jiawei Zhang 006 (CoRR, 2022)

Tightness without Counterexamples: A New Approach and New Results for Prophet Inequalities. - Jiashuo Jiang; Will Ma; Jiawei Zhang 006 (EC, 2023)

Constant Approximation for Network Revenue Management with Markovian-Correlated Customer Arrivals. - Jiashuo Jiang (CoRR, 2023)

Achieving High Individual Service Levels Without Safety Stock? Optimal Rationing Policy of Pooled Resources. - Jiashuo Jiang; Shixin Wang 006; Jiawei Zhang 006 (Oper. Res., 2023)

High-dimensional Linear Bandits with Knapsacks. - Wanteng Ma; Dong Xia; Jiashuo Jiang (ICML, 2024)

Achieving Õ(1/ε) Sample Complexity for Constrained Markov Decision Process. - Jiashuo Jiang; Yinyu Ye 001 (NeurIPS, 2024)

Constrained Online Two-stage Stochastic Optimization: Algorithm with (and without) Predictions. - Piao Hu; Jiashuo Jiang; Guodong Lyu; Hao Su (CoRR, 2024)

Regret Minimization and Statistical Inference in Online Decision Making with High-dimensional Covariates. - Congyuan Duan; Wanteng Ma; Jiashuo Jiang; Dong Xia (CoRR, 2024)

Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies. - Boxiao Chen; Jiashuo Jiang; Jiawei Zhang 006; Zhengyuan Zhou (Manag. Sci., 2024)

Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control. - Zifan Liu; Xinran Li; Shibo Chen 002; Gen Li 011; Jiashuo Jiang; Jun Zhang 004 (AISTATS, 2025)

Tight Guarantees for Multiunit Prophet Inequalities and Online Stochastic Knapsack. - Jiashuo Jiang; Will Ma; Jiawei Zhang 006 (Oper. Res., 2025)

Learning to Price with Resource Constraints: From Full Information to Machine-Learned Prices. - Ruicheng Ao; Jiashuo Jiang; David Simchi-Levi (CoRR, 2025)

Joint Pricing and Resource Allocation: An Optimal Online-Learning Approach. - Jianyu Xu; Xuan Wang; Yu-Xiang Wang; Jiashuo Jiang (CoRR, 2025)

Efficiently Solving Discounted MDPs with Predictions on Transition Matrices. - Lixing Lyu; Jiashuo Jiang; Wang Chi Cheung (CoRR, 2025)

Adaptive Bidding Policies for First-Price Auctions with Budget Constraints under Non-stationarity. - Yige Wang; Jiashuo Jiang (CoRR, 2025)

Adaptive Resolving Methods for Reinforcement Learning with Function Approximations. - Jiashuo Jiang; Yiming Zong; Yinyu Ye 001 (CoRR, 2025)

A Lyapunov Drift-Plus-Penalty Method Tailored for Reinforcement Learning with Queue Stability. - Wenhan Xu; Jiashuo Jiang; Lei Deng; Danny Hin-Kwok Tsang (CoRR, 2025)