Xi Chen

82 papers A* 14A 6Journal 54Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Technical Note - Fairness-Aware Online Price Discrimination with Nonparametric Demand Models.
Oper. Res.
Xi Chen, Jiameng Lyu, Xuan Zhang, Yuan Zhou
2026 J jnl
Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity.
CoRR
Elynn Chen, Xi Chen, Yi Zhang
2026 J jnl
Utility Fairness in Contextual Dynamic Pricing with Demand Learning.
Manag. Sci.
Xi Chen, David Simchi-Levi, Yining Wang
2025 J jnl
Bayesian Mechanism Design for Blockchain Transaction Fee Allocation.
Oper. Res.
Xi Chen, David Simchi-Levi, Zishuo Zhao, Yuan Zhou
2025 A* conf
Maximal Extractable Value in Batch Auctions.
EC
Mengqian Zhang, Yuhao Li, Xinyuan Sun, Elynn Y. Chen, Xi Chen
2025 J jnl
Stochastic Linear Bandits with Latent Heterogeneity.
CoRR
Elynn Y. Chen, Xi Chen, Wenbo Jing, Xiao Liu
2024 J jnl
Assortment Planning for Recommendations at Checkout Under Inventory Constraints.
Math. Oper. Res.
Xi Chen, Will Ma, David Simchi-Levi, Linwei Xin
2024 J jnl
Data-Driven Knowledge Transfer in Batch Q
CoRR
Elynn Y. Chen, Xi Chen, Wenbo Jing
2024 J jnl
Robust Dynamic Assortment Optimization in the Presence of Outlier Customers.
Oper. Res.
Xi Chen, Akshay Krishnamurthy, Yining Wang
2024 — conf
SoK: MEV Countermeasures.
DeFi@CCS
Sen Yang, Fan Zhang, Ken Huang, Xi Chen, Youwei Yang, Feng Zhu
2024 J jnl
Wasserstein Distributionally Robust Optimization and Variation Regularization.
Oper. Res.
Rui Gao, Xi Chen, Anton J. Kleywegt
2023 J jnl
Active Learning for Contextual Search with Binary Feedback.
Manag. Sci.
Xi Chen, Quanquan Liu, Yining Wang
2023 A* conf
Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model.
EC
Shuting Shen, Xi Chen, Ethan X. Fang, Junwei Lu
2023 J jnl
Differential Privacy in Personalized Pricing with Nonparametric Demand Models.
Oper. Res.
Xi Chen, Sentao Miao, Yining Wang
2023 — conf
MEV Makes Everyone Happy under Greedy Sequencing Rule.
DeFi@CCS
Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Y. Chen, Xi Chen, Xiaotie Deng
2023 J jnl
MEV Makes Everyone Happy under Greedy Sequencing Rule.
CoRR
Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Y. Chen, Xi Chen, Xiaotie Deng
2023 J jnl
Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers.
Oper. Res.
Xi Chen, Yining Wang
2023 J jnl
Utility Fairness in Contextual Dynamic Pricing with Demand Learning.
CoRR
Xi Chen, David Simchi-Levi, Yining Wang
2022 J jnl
A Statistical Learning Approach to Personalization in Revenue Management.
Manag. Sci.
Xi Chen, Zachary Owen, Clark Pixton, David Simchi-Levi
2022 J jnl
Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling.
J. Mach. Learn. Res.
Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang
2022 J jnl
Asymptotically Optimal Sequential Design for Rank Aggregation.
Math. Oper. Res.
Xi Chen, Yunxiao Chen, Xiaoou Li
2022 J jnl
Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation.
CoRR
Zishuo Zhao, Xi Chen, Yuan Zhou
2022 A* conf
Dynamic Car Dispatching and Pricing: Revenue and Fairness for Ridesharing Platforms.
IJCAI
Zishuo Zhao, Xi Chen, Xuefeng Zhang, Yuan Zhou
2022 J jnl
Dynamic Car Dispatching and Pricing: Revenue and Fairness for Ridesharing Platforms.
CoRR
Zishuo Zhao, Xi Chen, Xuefeng Zhang, Yuan Zhou
2022 J jnl
Fairness-aware Network Revenue Management with Demand Learning.
CoRR
Xi Chen, Jiameng Lyu, Yining Wang, Yuan Zhou
2022 J jnl
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning.
Manag. Sci.
Xi Chen, David Simchi-Levi, Yining Wang
2022 J jnl
SoK: MEV Countermeasures: Theory and Practice.
CoRR
Sen Yang, Fan Zhang, Ken Huang, Xi Chen, Youwei Yang, Feng Zhu
2021 J jnl
Differential Privacy in Personalized Pricing with Nonparametric Demand Models.
CoRR
Xi Chen, Sentao Miao, Yining Wang
2021 J jnl
Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models.
Math. Oper. Res.
Xi Chen, Yining Wang, Yuan Zhou
2021 J jnl
The Discrete Moment Problem with Nonconvex Shape Constraints.
Oper. Res.
Xi Chen, Simai He, Bo Jiang, Christopher Thomas Ryan, Teng Zhang
2021 A conf
Tight Regret Bounds for Infinite-armed Linear Contextual Bandits.
AISTATS
Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou
2020 A* conf
DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis.
ICDM
Chuheng Zhang, Yuanqi Li, Xi Chen, Yifei Jin, Pingzhong Tang, Jian Li
2020 J jnl
DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis.
CoRR
Chuheng Zhang, Yuanqi Li, Xi Chen, Yifei Jin, Pingzhong Tang, Jian Li
2020 J jnl
Dynamic Assortment Optimization with Changing Contextual Information.
J. Mach. Learn. Res.
Xi Chen, Yining Wang, Yuan Zhou
2020 J jnl
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning.
CoRR
Xi Chen, David Simchi-Levi, Yining Wang
2020 J jnl
Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing.
CoRR
Xi Chen, Yining Wang
2019 J jnl
Context-Based Dynamic Pricing with Online Clustering.
CoRR
Sentao Miao, Xi Chen, Xiuli Chao, Jiaxi Liu, Yidong Zhang
2019 J jnl
Large-Scale Markov Decision Problems via the Linear Programming Dual.
CoRR
Yasin Abbasi-Yadkori, Peter L. Bartlett, Xi Chen, Alan Malek
2019 J jnl
Optimal Design of Process Flexibility for General Production Systems.
Oper. Res.
Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou
2019 J jnl
Robust Dynamic Assortment Optimization in the Presence of Outlier Customers.
CoRR
Xi Chen, Akshay Krishnamurthy, Yining Wang
2019 J jnl
Technical Note - Nonstationary Stochastic Optimization Under
Oper. Res.
Xi Chen, Yining Wang, Yu-Xiang Wang
2018 A* conf
A Nearly Instance Optimal Algorithm for Top-
SODA
Xi Chen, Yuanzhi Li, Jieming Mao
2018 J jnl
A note on a tight lower bound for capacitated MNL-bandit assortment selection models.
Oper. Res. Lett.
Xi Chen, Yining Wang
2018 J jnl
Dynamic Assortment Optimization with Changing Contextual Information.
CoRR
Xi Chen, Yining Wang, Yuan Zhou
2018 J jnl
Dynamic Assortment Selection under the Nested Logit Models.
CoRR
Xi Chen, Yining Wang, Yuan Zhou
2018 A* conf
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models.
NeurIPS
Yining Wang, Xi Chen, Yuan Zhou
2018 J jnl
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models.
CoRR
Yining Wang, Xi Chen, Yuan Zhou
2018 J jnl
Optimal Design of Process Flexibility for General Production Systems.
CoRR
Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou
2018 J jnl
Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem.
IEEE Trans. Inf. Theory
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
2017 J jnl
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model.
CoRR
Xi Chen, Yuanzhi Li, Jieming Mao
2017 J jnl
A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models.
CoRR
Xi Chen, Yining Wang
2017 A* conf
Adaptive Multiple-Arm Identification.
ICML
Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou
2017 J jnl
Adaptive Multiple-Arm Identification.
CoRR
Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou
2017 A* conf
Competitive analysis of the top-
SODA
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
2017 J jnl
Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes.
CoRR
Xi Chen, Yining Wang, Yu-Xiang Wang
2017 J jnl
Wasserstein Distributional Robustness and Regularization in Statistical Learning.
CoRR
Rui Gao, Xi Chen, Anton J. Kleywegt
2016 J jnl
Competitive analysis of the top-K ranking problem.
CoRR
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
2015 J jnl
A trade execution model under a composite dynamic coherent risk measure.
Oper. Res. Lett.
Qihang Lin, Xi Chen, Javier Peña
2015 J jnl
Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders.
Oper. Res.
Xi Chen, Jiawei Zhang, Yuan Zhou
2014 J jnl
A smoothing stochastic gradient method for composite optimization.
Optim. Methods Softw.
Qihang Lin, Xi Chen, Javier Peña
2014 J jnl
A sparsity preserving stochastic gradient methods for sparse regression.
Comput. Optim. Appl.
Qihang Lin, Xi Chen, Javier Peña
2014 A* conf
Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing.
ICML
Yuan Zhou, Xi Chen, Jian Li
2013 — —
Learning with Sparcity: Structures, Optimization and Applications.
Xi Chen
2013 — conf
Variance Reduction for Stochastic Gradient Optimization.
NIPS
Chong Wang, Xi Chen, Alexander J. Smola, Eric P. Xing
2012 A conf
Adaptive Multi-task Sparse Learning with an Application to fMRI Study.
SDM
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell
2012 J jnl
Group Sparse Additive Models
CoRR
Junming Yin, Xi Chen, Eric P. Xing
2012 A* conf
Group Sparse Additive Models.
ICML
Junming Yin, Xi Chen, Eric P. Xing
2012 — conf
Optimal Regularized Dual Averaging Methods for Stochastic Optimization.
NIPS
Xi Chen, Qihang Lin, Javier Peña
2012 J jnl
Smoothing Proximal Gradient Method for General Structured Sparse Learning
CoRR
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
2012 A conf
Structured Sparse Canonical Correlation Analysis.
AISTATS
Xi Chen, Han Liu, Jaime G. Carbonell
2011 A* conf
Direct Robust Matrix Factorizatoin for Anomaly Detection.
ICDM
Liang Xiong, Xi Chen, Jeff G. Schneider
2011 A conf
Smoothing Proximal Gradient Method for General Structured Sparse Learning.
UAI
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
2011 A conf
Sparse Latent Semantic Analysis.
SDM
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell
2010 J jnl
An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity
CoRR
Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing
2010 J jnl
Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso
CoRR
Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing
2010 — conf
Graph-Valued Regression.
NIPS
Han Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman
2010 A* conf
Learning Preferences with Millions of Parameters by Enforcing Sparsity.
ICDM
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell
2010 A* conf
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.
AAAI
Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell
2010 — conf
Multivariate Dyadic Regression Trees for Sparse Learning Problems.
NIPS
Han Liu, Xi Chen
2010 A conf
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization.
SDM
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell
2009 A* conf
Accelerated Gradient Method for Multi-task Sparse Learning Problem.
ICDM
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell
2009 — conf
Nonparametric Greedy Algorithms for the Sparse Learning Problem.
NIPS
Han Liu, Xi Chen