Accelerated Gradient Method for Multi-task Sparse Learning Problem. - Xi Chen 010; Weike Pan; James T. Kwok; Jaime G. Carbonell (ICDM, 2009)

Nonparametric Greedy Algorithms for the Sparse Learning Problem. - Han Liu 001; Xi Chen 010 (NIPS, 2009)

Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis. - Xi Chen 010; Yan Liu 002; Han Liu 001; Jaime G. Carbonell (AAAI, 2010)

Learning Preferences with Millions of Parameters by Enforcing Sparsity. - Xi Chen 010; Bing Bai; Yanjun Qi; Qihang Lin; Jaime G. Carbonell (ICDM, 2010)

Multivariate Dyadic Regression Trees for Sparse Learning Problems. - Han Liu 001; Xi Chen 010 (NIPS, 2010)

Graph-Valued Regression. - Han Liu 001; Xi Chen 010; John D. Lafferty; Larry A. Wasserman (NIPS, 2010)

Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization. - Liang Xiong; Xi Chen 010; Tzu-Kuo Huang; Jeff G. Schneider; Jaime G. Carbonell (SDM, 2010)

Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso - Xi Chen 010; Seyoung Kim; Qihang Lin; Jaime G. Carbonell; Eric P. Xing (CoRR, 2010)

An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity - Xi Chen 010; Qihang Lin; Seyoung Kim; Javier Peña 001; Jaime G. Carbonell; Eric P. Xing (CoRR, 2010)

Direct Robust Matrix Factorizatoin for Anomaly Detection. - Liang Xiong; Xi Chen 010; Jeff G. Schneider (ICDM, 2011)

Sparse Latent Semantic Analysis. - Xi Chen 010; Yanjun Qi; Bing Bai; Qihang Lin; Jaime G. Carbonell (SDM, 2011)

Smoothing Proximal Gradient Method for General Structured Sparse Learning. - Xi Chen 010; Qihang Lin; Seyoung Kim; Jaime G. Carbonell; Eric P. Xing (UAI, 2011)

Group Sparse Additive Models. - Junming Yin; Xi Chen 010; Eric P. Xing (ICML, 2012)

Optimal Regularized Dual Averaging Methods for Stochastic Optimization. - Xi Chen 010; Qihang Lin; Javier Peña 001 (NIPS, 2012)

Adaptive Multi-task Sparse Learning with an Application to fMRI Study. - Xi Chen 010; Jingrui He; Rick Lawrence; Jaime G. Carbonell (SDM, 2012)

Structured Sparse Canonical Correlation Analysis. - Xi Chen 010; Han Liu 001; Jaime G. Carbonell (AISTATS, 2012)

Variance Reduction for Stochastic Gradient Optimization. - Chong Wang 002; Xi Chen 010; Alexander J. Smola; Eric P. Xing (NIPS, 2013)

Learning with Sparcity: Structures, Optimization and Applications. - Xi Chen 010 (2013)

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing. - Yuan Zhou 007; Xi Chen 010; Jian Li 015 (ICML, 2014)

A sparsity preserving stochastic gradient methods for sparse regression. - Qihang Lin; Xi Chen 010; Javier Peña 001 (Comput. Optim. Appl., 2014)

A smoothing stochastic gradient method for composite optimization. - Qihang Lin; Xi Chen 010; Javier Peña 001 (Optim. Methods Softw., 2014)

Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders. - Xi Chen 010; Jiawei Zhang 006; Yuan Zhou 007 (Oper. Res., 2015)

A trade execution model under a composite dynamic coherent risk measure. - Qihang Lin; Xi Chen 010; Javier Peña 001 (Oper. Res. Lett., 2015)

Competitive analysis of the top-K ranking problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (CoRR, 2016)

Adaptive Multiple-Arm Identification. - Jiecao Chen; Xi Chen 010; Qin Zhang 001; Yuan Zhou 007 (ICML, 2017)

Competitive analysis of the top-K ranking problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (SODA, 2017)

A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. - Xi Chen 010; Yuanzhi Li; Jieming Mao (CoRR, 2017)

Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes. - Xi Chen 010; Yining Wang 001; Yu-Xiang Wang 003 (CoRR, 2017)

A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models. - Xi Chen 010; Yining Wang 001 (CoRR, 2017)

Wasserstein Distributional Robustness and Regularization in Statistical Learning. - Rui Gao 001; Xi Chen 010; Anton J. Kleywegt (CoRR, 2017)

Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models. - Yining Wang 001; Xi Chen 010; Yuan Zhou 007 (NeurIPS, 2018)

A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. - Xi Chen 010; Yuanzhi Li; Jieming Mao (SODA, 2018)

Dynamic Assortment Selection under the Nested Logit Models. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (CoRR, 2018)

A note on a tight lower bound for capacitated MNL-bandit assortment selection models. - Xi Chen 010; Yining Wang 001 (Oper. Res. Lett., 2018)

Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (IEEE Trans. Inf. Theory, 2018)

Large-Scale Markov Decision Problems via the Linear Programming Dual. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Xi Chen 010; Alan Malek (CoRR, 2019)

Optimal Design of Process Flexibility for General Production Systems. - Xi Chen 010; Tengyu Ma 001; Jiawei Zhang 006; Yuan Zhou 007 (Oper. Res., 2019)

Technical Note - Nonstationary Stochastic Optimization Under Lp, q-Variation Measures. - Xi Chen 010; Yining Wang 001; Yu-Xiang Wang 003 (Oper. Res., 2019)

DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis. - Chuheng Zhang; Yuanqi Li; Xi Chen 010; Yifei Jin; Pingzhong Tang; Jian Li 015 (ICDM, 2020)

Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing. - Xi Chen 010; Yining Wang 001 (CoRR, 2020)

Dynamic Assortment Optimization with Changing Contextual Information. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (J. Mach. Learn. Res., 2020)

Tight Regret Bounds for Infinite-armed Linear Contextual Bandits. - Yingkai Li; Yining Wang 001; Xi Chen 010; Yuan Zhou 007 (AISTATS, 2021)

The Discrete Moment Problem with Nonconvex Shape Constraints. - Xi Chen 010; Simai He; Bo Jiang 007; Christopher Thomas Ryan; Teng Zhang (Oper. Res., 2021)

Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (Math. Oper. Res., 2021)

Dynamic Car Dispatching and Pricing: Revenue and Fairness for Ridesharing Platforms. - Zishuo Zhao; Xi Chen 010; Xuefeng Zhang; Yuan Zhou 007 (IJCAI, 2022)

Fairness-aware Network Revenue Management with Demand Learning. - Xi Chen 010; Jiameng Lyu; Yining Wang 001; Yuan Zhou 007 (CoRR, 2022)

Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation. - Zishuo Zhao; Xi Chen 010; Yuan Zhou 007 (CoRR, 2022)

SoK: MEV Countermeasures: Theory and Practice. - Sen Yang; Fan Zhang 022; Ken Huang; Xi Chen 010; Youwei Yang; Feng Zhu 023 (CoRR, 2022)

Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling. - Xi Chen 010; Bo Jiang 007; Tianyi Lin; Shuzhong Zhang (J. Mach. Learn. Res., 2022)

A Statistical Learning Approach to Personalization in Revenue Management. - Xi Chen 010; Zachary Owen; Clark Pixton; David Simchi-Levi (Manag. Sci., 2022)

Privacy-Preserving Dynamic Personalized Pricing with Demand Learning. - Xi Chen 010; David Simchi-Levi; Yining Wang 001 (Manag. Sci., 2022)

Asymptotically Optimal Sequential Design for Rank Aggregation. - Xi Chen 010; Yunxiao Chen; Xiaoou Li (Math. Oper. Res., 2022)

MEV Makes Everyone Happy under Greedy Sequencing Rule. - Yuhao Li 002; Mengqian Zhang; Jichen Li; Elynn Y. Chen; Xi Chen 010; Xiaotie Deng (DeFi@CCS, 2023)

Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model. - Shuting Shen; Xi Chen 010; Ethan X. Fang; Junwei Lu (EC, 2023)

Utility Fairness in Contextual Dynamic Pricing with Demand Learning. - Xi Chen 010; David Simchi-Levi; Yining Wang 001 (CoRR, 2023)

Differential Privacy in Personalized Pricing with Nonparametric Demand Models. - Xi Chen 010; Sentao Miao; Yining Wang 001 (Oper. Res., 2023)

Active Learning for Contextual Search with Binary Feedback. - Xi Chen 010; Quanquan Liu; Yining Wang 001 (Manag. Sci., 2023)

Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers. - Xi Chen 010; Yining Wang 001 (Oper. Res., 2023)

SoK: MEV Countermeasures. - Sen Yang; Fan Zhang 022; Ken Huang; Xi Chen 010; Youwei Yang; Feng Zhu 023 (DeFi@CCS, 2024)

Robust Dynamic Assortment Optimization in the Presence of Outlier Customers. - Xi Chen 010; Akshay Krishnamurthy; Yining Wang 001 (Oper. Res., 2024)

Wasserstein Distributionally Robust Optimization and Variation Regularization. - Rui Gao 001; Xi Chen 010; Anton J. Kleywegt (Oper. Res., 2024)

Assortment Planning for Recommendations at Checkout Under Inventory Constraints. - Xi Chen 010; Will Ma; David Simchi-Levi; Linwei Xin (Math. Oper. Res., 2024)

Maximal Extractable Value in Batch Auctions. - Mengqian Zhang; Yuhao Li 002; Xinyuan Sun; Elynn Y. Chen; Xi Chen 010 (EC, 2025)

Bayesian Mechanism Design for Blockchain Transaction Fee Allocation. - Xi Chen 010; David Simchi-Levi; Zishuo Zhao; Yuan Zhou 007 (Oper. Res., 2025)