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

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

Yonatan Gur, Ahmadreza Momeni

An agent facing sequential decisions that are characterized by partial feedback needs to strike a balance between maximizing immediate payoffs based on available information, and acquiring new information that may be essential for maximizing future...

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....