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2020 – today
- 2024
[j6]Nathan Kallus, Xiaojie Mao, Masatoshi Uehara:
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond. J. Mach. Learn. Res. 25: 16:1-16:59 (2024)- [i15]Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu:
Contextual Linear Optimization with Bandit Feedback. CoRR abs/2405.16564 (2024) - 2023
- [j5]Nathan Kallus
, Xiaojie Mao:
Stochastic Optimization Forests. Manag. Sci. 69(4): 1975-1994 (2023) - [c9]Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara:
Inference on Strongly Identified Functionals of Weakly Identified Functions. COLT 2023: 2265 - [c8]Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara:
Minimax Instrumental Variable Regression and L2 Convergence Guarantees without Identification or Closedness. COLT 2023: 2291-2318 - [i14]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 abs/2302.05404 (2023) - [i13]Yong Liang, Xiaojie Mao, Shiyuan Wang:
Online Joint Assortment-Inventory Optimization under MNL Choices. CoRR abs/2304.02022 (2023) - [i12]Jian Chen, Zhehao Li, Xiaojie Mao:
Learning under Selective Labels with Data from Heterogeneous Decision-makers: An Instrumental Variable Approach. CoRR abs/2306.07566 (2023) - [i11]Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara:
Source Condition Double Robust Inference on Functionals of Inverse Problems. CoRR abs/2307.13793 (2023) - 2022
- [j4]Yichun Hu, Nathan Kallus, Xiaojie Mao:
Smooth Contextual Bandits: Bridging the Parametric and Nondifferentiable Regret Regimes. Oper. Res. 70(6): 3261-3281 (2022) - [j3]Nathan Kallus, Xiaojie Mao, Angela Zhou:
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. Manag. Sci. 68(3): 1959-1981 (2022) - [j2]Yichun Hu, Nathan Kallus, Xiaojie Mao:
Fast Rates for Contextual Linear Optimization. Manag. Sci. 68(6): 4236-4245 (2022) - [c7]Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou:
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. ICML 2022: 10598-10632 - [i10]Nathan Kallus, Xiaojie Mao, Kaiwen Wang, Zhengyuan Zhou:
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning. CoRR abs/2202.09667 (2022) - 2021
- [i9]Nathan Kallus, Xiaojie Mao, Masatoshi Uehara:
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach. CoRR abs/2103.14029 (2021) - 2020
- [c6]Yichun Hu, Nathan Kallus, Xiaojie Mao:
Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. COLT 2020: 2007-2010 - [c5]Nathan Kallus, Xiaojie Mao, Angela Zhou:
Assessing algorithmic fairness with unobserved protected class using data combination. FAT* 2020: 110 - [i8]Nathan Kallus, Xiaojie Mao:
On the role of surrogates in the efficient estimation of treatment effects with limited outcome data. CoRR abs/2003.12408 (2020) - [i7]Nathan Kallus, Xiaojie Mao:
Stochastic Optimization Forests. CoRR abs/2008.07473 (2020) - [i6]Yichun Hu, Nathan Kallus, Xiaojie Mao:
Fast Rates for Contextual Linear Optimization. CoRR abs/2011.03030 (2020)
2010 – 2019
- 2019
- [c4]Nathan Kallus, Xiaojie Mao, Angela Zhou:
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. AISTATS 2019: 2281-2290 - [c3]Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell:
Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT 2019: 339-348 - [i5]Nathan Kallus, Xiaojie Mao, Angela Zhou:
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination. CoRR abs/1906.00285 (2019) - [i4]Yichun Hu, Nathan Kallus, Xiaojie Mao:
Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes. CoRR abs/1909.02553 (2019) - [i3]Nathan Kallus, Xiaojie Mao, Masatoshi Uehara:
Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond. CoRR abs/1912.12945 (2019) - 2018
- [j1]Zhiyu Qu, Xiaojie Mao, Zhian Deng:
Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network. IEEE Access 6: 43874-43884 (2018) - [c2]Zhaolei Liu, Xiaojie Mao, Zhian Deng:
Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder. CSPS (2) 2018: 752-761 - [c1]Nathan Kallus, Xiaojie Mao, Madeleine Udell:
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. NeurIPS 2018: 6921-6932 - [i2]Nathan Kallus, Xiaojie Mao, Madeleine Udell:
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. CoRR abs/1806.00811 (2018) - [i1]Nathan Kallus, Xiaojie Mao, Angela Zhou:
Interval Estimation of Individual-Level Causal Effects Under Unobserved Confounding. CoRR abs/1810.02894 (2018)
Coauthor Index
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