Search Results for author:
Found 8 papers, 3 papers with code
Targeting for long-term outcomes
We apply our approach in two large-scale proactive churn management experiments at The Boston Globe by targeting optimal discounts to its digital subscribers with the aim of maximizing long-term revenue.
Scalable bundling via dense product embeddings
We develop a new machine-learning-driven methodology for designing bundles in a large-scale, cross-category retail setting.
Seeding with Costly Network Information
We study the task of selecting $k$ nodes, in a social network of size $n$, to seed a diffusion with maximum expected spread size, under the independent cascade model with cascade probability $p$.
Social and Information Networks Computational Complexity Probability Physics and Society
Long ties accelerate noisy threshold-based contagions
To model the trade-off between long and short edges we analyze the rate of spread over networks that are the union of circular lattices and random graphs on $n$ nodes.
Social and Information Networks Probability Physics and Society 91D30, 05C80
Bias and high-dimensional adjustment in observational studies of peer effects
Naive observational estimators overstate peer effects by 320% and commonly used variables (e. g., demographics) offer little bias reduction, but adjusting for a measure of prior behaviors closely related to the focal behavior reduces bias by 91%.
Learning causal effects from many randomized experiments using regularized instrumental variables
Scientific and business practices are increasingly resulting in large collections of randomized experiments.
Thompson sampling with the online bootstrap
Subsequently, we detail why BTS using the online bootstrap is more scalable than regular Thompson sampling, and we show through simulation that BTS is more robust to a misspecified error distribution.
Social Influence in Social Advertising: Evidence from Field Experiments
This approach can increase ad efficacy for two main reasons: peers' affiliations reflect unobserved consumer characteristics, which are correlated along the social network; and the inclusion of social cues (i. e., peers' association with a brand) alongside ads affect responses via social influence processes.
Social and Information Networks Physics and Society Applications J.4; H.1.2
