Working Papers

These papers are working drafts of research which often appear in final form in academic journals. The published versions may differ from the working versions provided here.

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Di Wu, Harikesh S. Nair, Tong Geng
August 28, 2020

As households reduce discretionary spending in response to the COVID-19 pandemic, concerns are high that a resulting fall in aggregate demand can lead to a lasting recession post-COVID-19. Consequently, policies aimed at stimulating consumer spending...

Yonatan Gur, Ahmadreza Momeni

Sequential experiments are often designed to strike a balance between maximizing immediate payoffs based on available information, and acquiring new information that is essential for maximizing future payoffs. This trade-off is captured by the multi-armed...

Yonatan Gur, Ahmadreza Momeni, Stefan Wager

We study a non-parametric multi-armed bandit problem with stochastic covariates, where a key complexity driver is the smoothness of payoff functions with respect to covariates. Previous studies have focused on deriving minimax-optimal algorithms in cases...

Ruihuan Du, Yu Zhong, Harikesh S. Nair, Bo Cui, Ruyang Shou
January 30, 2019

This paper describes a practical system for Multi Touch Attribution (MTA) for use by a publisher of digital ads. We developed this system for, an eCommerce company, which is also a publisher of digital...

Matthew Corritore, Amir Goldberg, Sameer B. Srivastava
August 2018

How does cultural heterogeneity in an organization relate to its underlying capacity for execution and innovation? Existing literature often

Omar Besbes, Yonatan Gur, Assaf Zeevi

In a multi-armed bandit (MAB) problem a gambler needs to choose at each round of play one of K arms, each characterized by an unknown reward distribution. Reward realizations are only observed when an arm...

Santiago Balseiro, Yonatan Gur

In online advertising markets, advertisers often purchase ad placements through bidding in repeated auctions based on realized viewer information. We study how budget-constrained advertisers may compete in such sequential auctions in the presence of uncertainty...

Susan Athey, Mohsen Bayati, Nick Doudchenko, Guido W. Imbens, Khashayar Khosravi

In this paper we develop new methods for estimating causal effects in settings with panel data, where a subset of units are exposed to a treatment during a subset of periods, and the goal is...

Hamsa Bastani, Mohsen Bayati, Khashayar Khosravi

The contextual bandit literature has traditionally focused on algorithms that address the exploration-exploitation tradeoff. In particular, greedy algorithms that exploit current estimates without any exploration may be sub-optimal in general. However, exploration-free greedy algorithms...

Hamsa Bastani, Mohsen Bayati

Big data has enabled decision-makers to tailor decisions at the individual-level in a variety of domains such as personalized medicine and online advertising. This involves learning a model of decision rewards conditional on individual-specific covariates....