Xiaojie Mao - RankMe

32 papers A* 7A 1Journal 21Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Learning with Selectively Labeled Data from Multiple Decision-makers. ICML Jian Chen, Zhehao Li, Xiaojie Mao
2024	A*	`conf`	Contextual Linear Optimization with Bandit Feedback. NeurIPS Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu
2024	J	`jnl`	Contextual Linear Optimization with Bandit Feedback. CoRR Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu
2024	J	`jnl`	Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond. J. Mach. Learn. Res. Nathan Kallus, Xiaojie Mao, Masatoshi Uehara
2023	A*	`conf`	Inference on Strongly Identified Functionals of Weakly Identified Functions. COLT Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	J	`jnl`	Learning under Selective Labels with Data from Heterogeneous Decision-makers: An Instrumental Variable Approach. CoRR Jian Chen, Zhehao Li, Xiaojie Mao
2023	J	`jnl`	Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness. CoRR Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	A*	`conf`	Minimax Instrumental Variable Regression and L COLT Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	J	`jnl`	Online Joint Assortment-Inventory Optimization under MNL Choices. CoRR Yong Liang, Xiaojie Mao, Shiyuan Wang
2023	J	`jnl`	Source Condition Double Robust Inference on Functionals of Inverse Problems. CoRR Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023	J	`jnl`	Stochastic Optimization Forests. Manag. Sci. Nathan Kallus, Xiaojie Mao
2022	J	`jnl`	Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Manag. Sci. Nathan Kallus, Xiaojie Mao, Angela Zhou
2022	A*	`conf`	Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. ICML Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
2022	J	`jnl`	Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. CoRR Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou
2022	J	`jnl`	Fast Rates for Contextual Linear Optimization. Manag. Sci. Yichun Hu, Nathan Kallus, Xiaojie Mao
2022	J	`jnl`	Smooth Contextual Bandits: Bridging the Parametric and Nondifferentiable Regret Regimes. Oper. Res. Yichun Hu, Nathan Kallus, Xiaojie Mao
2021	J	`jnl`	Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach. CoRR Nathan Kallus, Xiaojie Mao, Masatoshi Uehara
2020	—	`conf`	Assessing algorithmic fairness with unobserved protected class using data combination. FAT* Nathan Kallus, Xiaojie Mao, Angela Zhou
2020	J	`jnl`	Fast Rates for Contextual Linear Optimization. CoRR Yichun Hu, Nathan Kallus, Xiaojie Mao
2020	J	`jnl`	On the role of surrogates in the efficient estimation of treatment effects with limited outcome data. CoRR Nathan Kallus, Xiaojie Mao
2020	A*	`conf`	Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. COLT Yichun Hu, Nathan Kallus, Xiaojie Mao
2020	J	`jnl`	Stochastic Optimization Forests. CoRR Nathan Kallus, Xiaojie Mao
2019	J	`jnl`	Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. CoRR Nathan Kallus, Xiaojie Mao, Angela Zhou
2019	—	`conf`	Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell
2019	A	`conf`	Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. AISTATS Nathan Kallus, Xiaojie Mao, Angela Zhou
2019	J	`jnl`	Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond. CoRR Nathan Kallus, Xiaojie Mao, Masatoshi Uehara
2019	J	`jnl`	Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. CoRR Yichun Hu, Nathan Kallus, Xiaojie Mao
2018	A*	`conf`	Causal Inference with Noisy and Missing Covariates via Matrix Factorization. NeurIPS Nathan Kallus, Xiaojie Mao, Madeleine Udell
2018	J	`jnl`	Causal Inference with Noisy and Missing Covariates via Matrix Factorization. CoRR Nathan Kallus, Xiaojie Mao, Madeleine Udell
2018	J	`jnl`	Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. CoRR Nathan Kallus, Xiaojie Mao, Angela Zhou
2018	J	`jnl`	Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network. IEEE Access Zhiyu Qu, Xiaojie Mao, Zhian Deng
2018	—	`conf`	Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder. CSPS (2) Zhaolei Liu, Xiaojie Mao, Zhian Deng