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06/26/2023
Off-Policy Evaluation of Ranking Policies under Diverse User Behavior
Ranking interfaces are everywhere in online platforms. There is thus an ...
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12/04/2022
Counterfactual Learning with General Data-generating Policies
Off-policy evaluation (OPE) attempts to predict the performance of count...
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11/25/2022
Policy-Adaptive Estimator Selection for Off-Policy Evaluation
Off-policy evaluation (OPE) aims to accurately evaluate the performance ...
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10/28/2022
SMART-EXAM: Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Dynamic treatment regimes (DTRs) are sequences of decision rules that re...
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02/03/2022
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
In real-world recommender systems and search engines, optimizing ranking...
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08/31/2021
Evaluating the Robustness of Off-Policy Evaluation
Off-policy Evaluation (OPE), or offline evaluation in general, evaluates...
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04/26/2021
Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules
Algorithms produce a growing portion of decisions and recommendations bo...
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04/15/2021
Curse of Democracy: Evidence from 2020
Countries with more democratic political regimes experienced greater GDP...
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12/31/2020
Breaking Ties: Regression Discontinuity Design Meets Market Design
Many schools in large urban districts have more applicants than seats. C...
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08/17/2020
A Large-scale Open Dataset for Bandit Algorithms
We build and publicize the Open Bandit Dataset and Pipeline to facilitat...
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02/20/2020
Safe Counterfactual Reinforcement Learning
We develop a method for predicting the performance of reinforcement lear...
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02/13/2020
Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm
Many scientific experiments have an interest in the estimation of the av...
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09/10/2018