Offline Multi-Action Policy Learning: Generalization and Optimization

10 October 2018

Papers citing "Offline Multi-Action Policy Learning: Generalization and Optimization"

20 / 20 papers shown

Title
Doubly Robust Fusion of Many Treatments for Policy Learning Ke Zhu Jianing Chu I. Lipkovich Wenyu Ye Shu Yang 34 0 0 12 May 2025
Contextual Linear Optimization with Bandit Feedback Yichun Hu Nathan Kallus Xiaojie Mao Yanchen Wu 35 0 0 26 May 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 42 3 0 28 Feb 2024
Individualized Policy Evaluation and Learning under Clustered Network Interference Yi Zhang Kosuke Imai OffRL 42 1 0 04 Nov 2023
Learning Prescriptive ReLU Networks Wei-Ju Sun Asterios Tsiourvas 21 2 0 01 Jun 2023
Tight Mixed-Integer Optimization Formulations for Prescriptive Trees Max Biggs Georgia Perakis 6 1 0 28 Feb 2023
Policy learning "without'' overlap: Pessimism and generalized empirical Bernstein's inequality Ying Jin Zhimei Ren Zhuoran Yang Zhaoran Wang OffRL 32 25 0 19 Dec 2022
Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning Susan Athey Undral Byambadalai Vitor Hadad Sanath Kumar Krishnamurthy Weiwen Leung Joseph Jay Williams 35 13 0 22 Nov 2022
Risk-Sensitive Markov Decision Processes with Long-Run CVaR Criterion L. Xia Peter Glynn 27 4 0 17 Oct 2022
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency Wenlong Mou Martin J. Wainwright Peter L. Bartlett OffRL 39 11 0 26 Sep 2022
Learning from a Biased Sample Roshni Sahoo Lihua Lei Stefan Wager 27 17 0 05 Sep 2022
Interpretable Off-Policy Learning via Hyperbox Search D. Tschernutter Tobias Hatt Stefan Feuerriegel OffRL CML 50 6 0 04 Mar 2022
Generalized Causal Tree for Uplift Modeling Preetam Nandy Xiufan Yu Wanjun Liu Ye Tu Kinjal Basu S. Chatterjee CML 29 3 0 04 Feb 2022
Loss Functions for Discrete Contextual Pricing with Observational Data Max Biggs Ruijiang Gao Wei-Ju Sun 31 10 0 18 Nov 2021
Interpretable Personalized Experimentation Han Wu S. Tan Weiwei Li Mia Garrard Adam Obeng Drew Dimmery Shaun Singh Hanson Wang Daniel R. Jiang E. Bakshy 33 5 0 05 Nov 2021
Efficient Learning of Optimal Individualized Treatment Rules for Heteroscedastic or Misspecified Treatment-Free Effect Models Weibin Mo Yufeng Liu 20 9 0 06 Sep 2021
Policy Learning with Adaptively Collected Data Ruohan Zhan Zhimei Ren Susan Athey Zhengyuan Zhou OffRL 40 27 0 05 May 2021
Stochastic Optimization Forests Nathan Kallus Xiaojie Mao 32 48 0 17 Aug 2020
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond Nathan Kallus Xiaojie Mao Masatoshi Uehara 25 25 0 30 Dec 2019
Policy Targeting under Network Interference Davide Viviano 38 33 0 24 Jun 2019