Xi Chen

According to our database, Xi Chen authored at least 45 papers between 2009 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers.

Xi Chen, Yining Wang

Oper. Res., July, 2023

Active Learning for Contextual Search with Binary Feedback.

Xi Chen, Quanquan Liu, Yining Wang

Manag. Sci., April, 2023

Differential Privacy in Personalized Pricing with Nonparametric Demand Models.

Xi Chen, Sentao Miao, Yining Wang

Oper. Res., March, 2023

Utility Fairness in Contextual Dynamic Pricing with Demand Learning.

Xi Chen, David Simchi-Levi, Yining Wang

CoRR, 2023

Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model.

Shuting Shen, Xi Chen, Ethan X. Fang, Junwei Lu

Proceedings of the 24th ACM Conference on Economics and Computation, 2023

MEV Makes Everyone Happy under Greedy Sequencing Rule.

Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, Xiaotie Deng

Proceedings of the 2023 Workshop on Decentralized Finance and Security, 2023

2022

Asymptotically Optimal Sequential Design for Rank Aggregation.

Xi Chen, Yunxiao Chen, Xiaoou Li

Math. Oper. Res., 2022

Privacy-Preserving Dynamic Personalized Pricing with Demand Learning.

Xi Chen, David Simchi-Levi, Yining Wang

Manag. Sci., 2022

A Statistical Learning Approach to Personalization in Revenue Management.

Xi Chen, Zachary Owen, Clark Pixton, David Simchi-Levi

Manag. Sci., 2022

Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling.

Xi Chen, Bo Jiang, Tianyi Lin, Shuzhong Zhang

J. Mach. Learn. Res., 2022

Fairness-aware Network Revenue Management with Demand Learning.

Xi Chen, Jiameng Lyu, Yining Wang, Yuan Zhou

CoRR, 2022

2021

Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models.

Xi Chen, Yining Wang, Yuan Zhou

Math. Oper. Res., 2021

The Discrete Moment Problem with Nonconvex Shape Constraints.

Xi Chen, Simai He, Bo Jiang, Christopher Thomas Ryan, Teng Zhang

Oper. Res., 2021

2020

Dynamic Assortment Optimization with Changing Contextual Information.

Xi Chen, Yining Wang, Yuan Zhou

J. Mach. Learn. Res., 2020

Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing.

Xi Chen, Yining Wang

CoRR, 2020

DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis.

Chuheng Zhang, Yuanqi Li, Xi Chen, Yifei Jin, Pingzhong Tang, Jian Li

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Technical Note - Nonstationary Stochastic Optimization Under <i>L</i>_{<i>p, q</i>}-Variation Measures.

Xi Chen, Yining Wang, Yu-Xiang Wang

Oper. Res., 2019

Optimal Design of Process Flexibility for General Production Systems.

Xi Chen, Tengyu Ma, Jiawei Zhang, Yuan Zhou

Oper. Res., 2019

Robust Dynamic Assortment Optimization in the Presence of Outlier Customers.

Xi Chen, Akshay Krishnamurthy, Yining Wang

CoRR, 2019

Large-Scale Markov Decision Problems via the Linear Programming Dual.

Yasin Abbasi-Yadkori, Peter L. Bartlett, Xi Chen, Alan Malek

CoRR, 2019

2018

Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem.

Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider

IEEE Trans. Inf. Theory, 2018

A note on a tight lower bound for capacitated MNL-bandit assortment selection models.

Xi Chen, Yining Wang

Oper. Res. Lett., 2018

Dynamic Assortment Selection under the Nested Logit Models.

Xi Chen, Yining Wang, Yuan Zhou

CoRR, 2018

A Nearly Instance Optimal Algorithm for Top-<i>k</i> Ranking under the Multinomial Logit Model.

Xi Chen, Yuanzhi Li, Jieming Mao

Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models.

Yining Wang, Xi Chen, Yuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models.

Xi Chen, Yining Wang

CoRR, 2017

Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes.

Xi Chen, Yining Wang, Yu-Xiang Wang

CoRR, 2017

A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model.

Xi Chen, Yuanzhi Li, Jieming Mao

CoRR, 2017

Competitive analysis of the top-<i>K</i> ranking problem.

Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider

Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

Adaptive Multiple-Arm Identification.

Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Competitive analysis of the top-K ranking problem.

Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider

CoRR, 2016

2015

Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders.

Xi Chen, Jiawei Zhang, Yuan Zhou

Oper. Res., 2015

2014

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing.

Yuan Zhou, Xi Chen, Jian Li

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Learning with Sparcity: Structures, Optimization and Applications.

Xi Chen

PhD thesis, 2013

2012

Structured Sparse Canonical Correlation Analysis.

Xi Chen, Han Liu, Jaime G. Carbonell

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Adaptive Multi-task Sparse Learning with an Application to fMRI Study.

Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbonell

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

2011

Smoothing Proximal Gradient Method for General Structured Sparse Learning.

Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing

Proceedings of the UAI 2011, 2011

Sparse Latent Semantic Analysis.

Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Direct Robust Matrix Factorizatoin for Anomaly Detection.

Liang Xiong, Xi Chen, Jeff G. Schneider

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity

Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing

CoRR, 2010

Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso

Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing

CoRR, 2010

Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization.

Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell

Proceedings of the SIAM International Conference on Data Mining, 2010

Learning Preferences with Millions of Parameters by Enforcing Sparsity.

Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell

Proceedings of the ICDM 2010, 2010

Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.

Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Accelerated Gradient Method for Multi-task Sparse Learning Problem.

Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell

Proceedings of the ICDM 2009, 2009