Xi Chen - RankMe

82 papers A* 14A 6Journal 54Unranked 7

Year	Rank	Type	Title / 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