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07/05/2023
Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
Simple regret minimization is a critical problem in learning optimal tre...
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06/21/2023
Qini Curves for Multi-Armed Treatment Rules
Qini curves have emerged as an attractive and popular approach for evalu...
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05/21/2023
Federated Offline Policy Learning with Heterogeneous Observational Data
We consider the problem of learning personalized decision policies on ob...
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04/04/2023
Torch-Choice: A PyTorch Package for Large-Scale Choice Modelling with Python
The is an open-source library for flexible, fast choice modeling with P...
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12/27/2022
Battling the Coronavirus Infodemic Among Social Media Users in Africa
During a global pandemic, how can we best prompt social media users to d...
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11/22/2022
Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning
We design and implement an adaptive experiment (a “contextual bandit”) t...
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03/30/2022
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracle
Many popular contextual bandit algorithms estimate reward models to info...
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02/16/2022
Learning Transferrable Representations of Career Trajectories for Economic Prediction
Understanding career trajectories – the sequences of jobs that individua...
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09/06/2021
Semiparametric Estimation of Treatment Effects in Randomized Experiments
We develop new semiparametric methods for estimating treatment effects. ...
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07/25/2021
Federated Causal Inference in Heterogeneous Observational Data
Analyzing observational data from multiple sources can be useful for inc...
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06/11/2021
Optimal Model Selection in Contextual Bandits with Many Classes via Offline Oracles
We study the problem of model selection for contextual bandits, in which...
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06/03/2021
Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits
It has become increasingly common for data to be collected adaptively, f...
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05/05/2021
Policy Learning with Adaptively Collected Data
Learning optimal policies from historical data enables the gains from pe...
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02/26/2021
Adapting to misspecification in contextual bandits with offline regression oracles
Computationally efficient contextual bandits are often based on estimati...
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10/25/2020
Tractable contextual bandits beyond realizability
Tractable contextual bandit algorithms often rely on the realizability a...
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06/17/2020
Combining Experimental and Observational Data to Estimate Treatment Effects on Long Term Outcomes
There has been an increase in interest in experimental evaluations to es...
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02/23/2020
Survey Bandits with Regret Guarantees
We consider a variant of the contextual bandit problem. In standard cont...
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01/31/2020
Stable Prediction with Model Misspecification and Agnostic Distribution Shift
For many machine learning algorithms, two main assumptions are required ...
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11/09/2019
Optimal Experimental Design for Staggered Rollouts
Experimentation has become an increasingly prevalent tool for guiding po...
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11/07/2019
Confidence Intervals for Policy Evaluation in Adaptive Experiments
Adaptive experiments can result in considerable cost savings in multi-ar...
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09/05/2019
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations
Researchers often use artificial data to assess the performance of new e...
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08/26/2019
Sufficient Representations for Categorical Variables
Many learning algorithms require categorical data to be transformed into...
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06/06/2019
Counterfactual Inference for Consumer Choice Across Many Product Categories
This paper proposes a method for estimating consumer preferences among d...
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03/24/2019
Machine Learning Methods Economists Should Know About
We discuss the relevance of the recent Machine Learning (ML) literature ...
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02/20/2019
Estimating Treatment Effects with Causal Forests: An Application
We apply causal forests to a dataset derived from the National Study of ...
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12/24/2018
Synthetic Difference in Differences
We present a new perspective on the Synthetic Control (SC) method as a w...
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12/15/2018
Balanced Linear Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of t...
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10/10/2018
Offline Multi-Action Policy Learning: Generalization and Optimization
In many settings, a decision-maker wishes to learn a rule, or policy, th...
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08/15/2018
Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption
In this paper we study estimation of and inference for average treatment...
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07/30/2018
Local Linear Forests
Random forests are a powerful method for non-parametric regression, but ...
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06/16/2018
Stable Prediction across Unknown Environments
In many important machine learning applications, the training distributi...
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01/22/2018
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data
This paper analyzes consumer choices over lunchtime restaurants using da...
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11/19/2017
Estimation Considerations in Contextual Bandits
Contextual bandit algorithms seek to learn a personalized treatment assi...
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11/09/2017
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements
We develop SHOPPER, a sequential probabilistic model of market baskets. ...
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10/27/2017
Matrix Completion Methods for Causal Panel Data Models
In this paper we develop new methods for estimating causal effects in se...
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09/28/2017
Structured Embedding Models for Grouped Data
Word embeddings are a powerful approach for analyzing language, and expo...
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02/09/2017
Efficient Policy Learning
We consider the problem of using observational data to learn treatment a...
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10/05/2016
Generalized Random Forests
We propose generalized random forests, a method for non-parametric stati...
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03/30/2016
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
Estimating the long-term effects of treatments is of interest in many fi...
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10/14/2015
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Many scientific and engineering challenges -- ranging from personalized ...
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04/05/2015
