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Scalable Approximations for Generalized Linear Problems
In stochastic optimization, the population risk is generally approximated by the empirical risk which is in turn minimized by an iterative algorithm. However, in the large-scale setting, empirical risk minimization may be computationally…
Economists (and Economics) in Tech Companies
As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies – tackling problems such as platform design, strategy, pricing, and policy. Over…
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data
We estimate a model of consumer choices over restaurants using data from several thousand anonymous mobile phone users. Restaurants have latent characteristics (whose distribution may depend on restaurant observables) that affect consumers’ mean…
Data Uncertainty in Markov Chains: Application to Cost-effectiveness Analyses of Medical Innovations
Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When Markov chains are used as a modeling framework for such studies, this data inadequacy can manifest itself as imprecise estimates for many elements of the…
Statistical Analysis of a Low-cost Method for Multiple Disease Prediction
Early identification of individuals at risk for chronic diseases is of significant clinical value. Early detection provides the opportunity to slow the pace of a condition, and thus help individuals to improve or maintain their quality of…