STAMP: A Strategy-proof Approximation auction Mechanism for Spatially reusable Items in wireless networks. - Ruihao Zhu; Fan Wu 006; Guihai Chen (GLOBECOM, 2013)

SAFE: A Strategy-Proof Auction Mechanism for Multi-radio, Multi-channel Spectrum Allocation. - Ruihao Zhu; Fan Wu 006; Guihai Chen (WASA, 2013)

Differentially private spectrum auction with approximate revenue maximization. - Ruihao Zhu; Zhijing Li 001; Fan Wu 006; Kang G. Shin; Guihai Chen (MobiHoc, 2014)

Differentially private and strategy-proof spectrum auction with approximate revenue maximization. - Ruihao Zhu; Kang G. Shin (INFOCOM, 2015)

Threshold Bandits, With and Without Censored Feedback. - Jacob D. Abernethy; Kareem Amin 002; Ruihao Zhu (NIPS, 2016)

Coresets for differentially private k-means clustering and applications to privacy in mobile sensor networks. - Dan Feldman; Chongyuan Xiang; Ruihao Zhu; Daniela Rus (IPSN, 2017)

Learning to Route Efficiently with End-to-End Feedback: The Value of Networked Structure. - Ruihao Zhu; Eytan H. Modiano (CoRR, 2018)

Learning to Optimize under Non-Stationarity. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (AISTATS, 2019)

Meta Dynamic Pricing: Learning Across Experiments. - Hamsa Bastani; David Simchi-Levi; Ruihao Zhu (CoRR, 2019)

Hedging the Drift: Learning to Optimize under Non-Stationarity. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (CoRR, 2019)

Reinforcement Learning under Drift. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (CoRR, 2019)

Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (ICML, 2020)

Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (CoRR, 2020)

A soft quadruped robot enabled by continuum actuators. - Seshagopalan Thorapalli Muralidharan; Ruihao Zhu; Qinglei Ji; Lei Feng 002; Xi Vincent Wang; Lihui Wang 001 (CASE, 2021)

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (ICML, 2021)

Safe Optimal Design with Applications in Policy Learning. - Ruihao Zhu; Branislav Kveton (CoRR, 2021)

Safe Optimal Design with Applications in Off-Policy Learning. - Ruihao Zhu; Branislav Kveton (AISTATS, 2022)

Risk-Aware Linear Bandits with Application in Smart Order Routing. - Jingwei Ji; Renyuan Xu; Ruihao Zhu (ICAIF, 2022)

Risk-Aware Linear Bandits: Theory and Applications in Smart Order Routing. - Jingwei Ji; Renyuan Xu; Ruihao Zhu (CoRR, 2022)

Phase Transitions in Learning and Earning under Price Protection Guarantee. - Qing Feng; Ruihao Zhu; Stefanus Jasin (CoRR, 2022)

Learning to Price Supply Chain Contracts against a Learning Retailer. - Xuejun Zhao; Ruihao Zhu; William B. Haskell 001 (CoRR, 2022)

Meta Dynamic Pricing: Transfer Learning Across Experiments. - Hamsa Bastani; David Simchi-Levi; Ruihao Zhu (Manag. Sci., 2022)

Hedging the Drift: Learning to Optimize Under Nonstationarity. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (Manag. Sci., 2022)

MERIT: A Merchant Incentive Ranking Model for Hotel Search & Ranking. - Shigang Quan; Hailong Tan; Shui Liu; Zhenzhe Zheng; Ruihao Zhu; Liangyue Li; Quan Lu; Fan Wu 006 (CIKM, 2023)

Trigger Warning Labeling with RoBERTa and Resampling for Distressing Content Detection. - Haojie Cao; Zhongyuan Han; Guiyuan Cao; Ruihao Zhu; Yongqi Liang; Siman Liu; Minhua Huang; Haihao Yu (CLEF (Working Notes), 2023)

LINet: A Location and Intention-Aware Neural Network for Hotel Group Recommendation. - Ruitao Zhu; Detao Lv; Yao Yu; Ruihao Zhu; Zhenzhe Zheng; Ke Bu; Quan Lu; Fan Wu 006 (WWW, 2023)

Efficient and Interpretable Bandit Algorithms. - Subhojyoti Mukherjee; Ruihao Zhu; Branislav Kveton (CoRR, 2023)

Nonstationary Reinforcement Learning: The Blessing of (More) Optimism. - Wang Chi Cheung; David Simchi-Levi; Ruihao Zhu (Manag. Sci., 2023)

User Experience Design Professionals' Perceptions of Generative Artificial Intelligence. - Jie Li 064; Hancheng Cao; Laura Lin; Youyang Hou; Ruihao Zhu; Abdallah El Ali (CHI, 2024)

Conspiracy Theory Text Classification Based on CT-BERT and BETO Models. - Jiahong Huang; Zhongyuan Han; Ruihao Zhu; Mingcan Guo; Kaiyin Sun (CLEF (Working Notes), 2024)

Satisficing Exploration in Bandit Optimization. - Qing Feng; Tianyi Ma; Ruihao Zhu (CoRR, 2024)

Reward Learning From Preference With Ties. - Jinsong Liu; Dongdong Ge; Ruihao Zhu (CoRR, 2024)

Calibrating Sales Forecasts in a Pandemic Using Competitive Online Nonparametric Regression. - David Simchi-Levi; Rui Sun; Michelle Xiao Wu; Ruihao Zhu (Manag. Sci., 2024)

Satisficing Regret Minimization in Bandits. - Qing Feng; Tianyi Ma; Ruihao Zhu (ICLR, 2025)

Temporal Fairness in Learning and Earning: Price Protection Guarantee and Phase Transitions. - Qing Feng; Ruihao Zhu; Stefanus Jasin (Oper. Res., 2025)

Model-Free Nonstationary Reinforcement Learning: Near-Optimal Regret and Applications in Multiagent Reinforcement Learning and Inventory Control. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (Manag. Sci., 2025)

Thompson Sampling for Repeated Newsvendor. - Weizhou Zhang; Chen Li; Hanzhang Qin; Yunbei Xu; Ruihao Zhu (CoRR, 2025)

Multi-Armed Bandits With Machine Learning-Generated Surrogate Rewards. - Wenlong Ji; Yihan Pan; Ruihao Zhu; Lihua Lei (CoRR, 2025)

Contextual Online Pricing with (Biased) Offline Data. - Yixuan Zhang; Ruihao Zhu; Qiaomin Xie (CoRR, 2025)