Xi Chen

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 38

Top Topics

Dynamic Pricing

Multinomial Logit

Linear Programming

Rank Aggregation

Top Venues

Math. Oper. Res.

Publications

Rui Gao, Xi Chen, Anton J. Kleywegt
Wasserstein Distributionally Robust Optimization and Variation Regularization. Oper. Res. 72 (3) (2024)
Xi Chen, Will Ma, David Simchi-Levi, Linwei Xin
Assortment Planning for Recommendations at Checkout Under Inventory Constraints. Math. Oper. Res. 49 (1) (2024)
Xi Chen, Akshay Krishnamurthy, Yining Wang
Robust Dynamic Assortment Optimization in the Presence of Outlier Customers. Oper. Res. 72 (3) (2024)
Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, Xiaotie Deng
MEV Makes Everyone Happy under Greedy Sequencing Rule. DeFi@CCS (2023)
Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, Xiaotie Deng
MEV Makes Everyone Happy under Greedy Sequencing Rule. CoRR (2023)
Shuting Shen, Xi Chen, Ethan X. Fang, Junwei Lu
Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model. EC (2023)
Xi Chen, Quanquan Liu, Yining Wang
Active Learning for Contextual Search with Binary Feedback. Manag. Sci. 69 (4) (2023)
Xi Chen, Yining Wang
Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers. Oper. Res. 71 (4) (2023)
Xi Chen, David Simchi-Levi, Yining Wang
Utility Fairness in Contextual Dynamic Pricing with Demand Learning. CoRR (2023)
Xi Chen, Sentao Miao, Yining Wang
Differential Privacy in Personalized Pricing with Nonparametric Demand Models. Oper. Res. 71 (2) (2023)
Xi Chen, Zachary Owen, Clark Pixton, David Simchi-Levi
A Statistical Learning Approach to Personalization in Revenue Management. Manag. Sci. 68 (3) (2022)
Xi Chen, Yunxiao Chen, Xiaoou Li
Asymptotically Optimal Sequential Design for Rank Aggregation. Math. Oper. Res. 47 (3) (2022)
Xi Chen, Jiameng Lyu, Yining Wang, Yuan Zhou
Fairness-aware Network Revenue Management with Demand Learning. CoRR (2022)
Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang
Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling. J. Mach. Learn. Res. 23 (2022)
Xi Chen, David Simchi-Levi, Yining Wang
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning. Manag. Sci. 68 (7) (2022)
Xi Chen, Yining Wang, Yuan Zhou
Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models. Math. Oper. Res. 46 (4) (2021)
Xi Chen, Simai He, Bo Jiang, Christopher Thomas Ryan, Teng Zhang
The Discrete Moment Problem with Nonconvex Shape Constraints. Oper. Res. 69 (1) (2021)
Xi Chen, Yining Wang
Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing. CoRR (2020)
Xi Chen, Yining Wang, Yuan Zhou
Dynamic Assortment Optimization with Changing Contextual Information. J. Mach. Learn. Res. 21 (2020)
Xi Chen, Yining Wang, Yu-Xiang Wang
-Variation Measures. Oper. Res. 67 (6) (2019)
Xi Chen, Akshay Krishnamurthy, Yining Wang
Robust Dynamic Assortment Optimization in the Presence of Outlier Customers. CoRR (2019)
Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou
Optimal Design of Process Flexibility for General Production Systems. Oper. Res. 67 (2) (2019)
Yasin Abbasi-Yadkori, Peter L. Bartlett, Xi Chen, Alan Malek
Large-Scale Markov Decision Problems via the Linear Programming Dual. CoRR (2019)
Yining Wang, Xi Chen, Yuan Zhou
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models. CoRR (2018)
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem. IEEE Trans. Inf. Theory 64 (9) (2018)
Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou
Optimal Design of Process Flexibility for General Production Systems. CoRR (2018)
Xi Chen, Yuanzhi Li, Jieming Mao
Ranking under the Multinomial Logit Model. SODA (2018)
Xi Chen, Yining Wang, Yuan Zhou
Dynamic Assortment Selection under the Nested Logit Models. CoRR (2018)
Xi Chen, Yining Wang
A note on a tight lower bound for capacitated MNL-bandit assortment selection models. Oper. Res. Lett. 46 (5) (2018)
Xi Chen, Yining Wang, Yuan Zhou
Dynamic Assortment Optimization with Changing Contextual Information. CoRR (2018)
Yining Wang, Xi Chen, Yuan Zhou
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models. NeurIPS (2018)
Xi Chen, Yuanzhi Li, Jieming Mao
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. CoRR (2017)
Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou
Adaptive Multiple-Arm Identification. CoRR (2017)
Xi Chen, Yining Wang
A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models. CoRR (2017)
Xi Chen, Yining Wang, Yu-Xiang Wang
Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes. CoRR (2017)
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
ranking problem. SODA (2017)
Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou
Adaptive Multiple-Arm Identification. ICML (2017)
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
Competitive analysis of the top-K ranking problem. CoRR (2016)
Xi Chen, Jiawei Zhang, Yuan Zhou
Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders. Oper. Res. 63 (5) (2015)
Yuan Zhou, Xi Chen, Jian Li
Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing. ICML (2014)
Xi Chen, Han Liu, Jaime G. Carbonell
Structured Sparse Canonical Correlation Analysis. AISTATS (2012)
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell
Adaptive Multi-task Sparse Learning with an Application to fMRI Study. SDM (2012)
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
Smoothing Proximal Gradient Method for General Structured Sparse Learning CoRR (2012)
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
Smoothing Proximal Gradient Method for General Structured Sparse Learning. UAI (2011)
Liang Xiong, Xi Chen, Jeff G. Schneider
Direct Robust Matrix Factorizatoin for Anomaly Detection. ICDM (2011)
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell
Sparse Latent Semantic Analysis. SDM (2011)
Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis. AAAI (2010)
Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing
An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity CoRR (2010)
Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing
Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso CoRR (2010)
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization. SDM (2010)
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell
Learning Preferences with Millions of Parameters by Enforcing Sparsity. ICDM (2010)
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell
Accelerated Gradient Method for Multi-task Sparse Learning Problem. ICDM (2009)