Xiaojie Mao

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 29

Top Topics

Multi Armed Bandit Problems

Top Venues

Publications

Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu
Contextual Linear Optimization with Bandit Feedback. CoRR (2024)
Yong Liang, Xiaojie Mao, Shiyuan Wang
Online Joint Assortment-Inventory Optimization under MNL Choices. CoRR (2023)
Nathan Kallus, Xiaojie Mao
Stochastic Optimization Forests. Manag. Sci. 69 (4) (2023)
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
Convergence Guarantees without Identification or Closedness. COLT (2023)
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
Inference on Strongly Identified Functionals of Weakly Identified Functions. COLT (2023)
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
Source Condition Double Robust Inference on Functionals of Inverse Problems. CoRR (2023)
Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness. CoRR (2023)
Jian Chen, Zhehao Li, Xiaojie Mao
Learning under Selective Labels with Heterogeneous Decision-makers: An Instrumental Variable Approach. CoRR (2023)
Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. CoRR (2022)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Manag. Sci. 68 (3) (2022)
Yichun Hu, Nathan Kallus, Xiaojie Mao
Smooth Contextual Bandits: Bridging the Parametric and Nondifferentiable Regret Regimes. Oper. Res. 70 (6) (2022)
Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. ICML (2022)
Yichun Hu, Nathan Kallus, Xiaojie Mao
Fast Rates for Contextual Linear Optimization. Manag. Sci. 68 (6) (2022)
Nathan Kallus, Xiaojie Mao, Masatoshi Uehara
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach. CoRR (2021)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing algorithmic fairness with unobserved protected class using data combination. FAT* (2020)
Nathan Kallus, Xiaojie Mao
Stochastic Optimization Forests. CoRR (2020)
Yichun Hu, Nathan Kallus, Xiaojie Mao
Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. COLT (2020)
Nathan Kallus, Xiaojie Mao
On the role of surrogates in the efficient estimation of treatment effects with limited outcome data. CoRR (2020)
Yichun Hu, Nathan Kallus, Xiaojie Mao
Fast Rates for Contextual Linear Optimization. CoRR (2020)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. CoRR (2019)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. AISTATS (2019)
Yichun Hu, Nathan Kallus, Xiaojie Mao
Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. CoRR (2019)
Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell
Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT (2019)
Nathan Kallus, Xiaojie Mao, Masatoshi Uehara
Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond. CoRR (2019)
Nathan Kallus, Xiaojie Mao, Angela Zhou
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. CoRR (2018)
Zhiyu Qu, Xiaojie Mao, Zhian Deng
Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network. IEEE Access 6 (2018)
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. NeurIPS (2018)
Zhaolei Liu, Xiaojie Mao, Zhian Deng
Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder. CSPS (2) (2018)
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. CoRR (2018)