Zero-shot causal learning
Predicting how different interventions will causally affect a specific individual is important in
a variety of domains such as personalized medicine, public policy, and online marketing …
a variety of domains such as personalized medicine, public policy, and online marketing …
Semi-parametric estimation of treatment effects in randomised experiments
We develop new semi-parametric methods for estimating treatment effects. We focus on
settings where the outcome distributions may be thick tailed, where treatment effects may be …
settings where the outcome distributions may be thick tailed, where treatment effects may be …
Neural Coordination and Capacity Control for Inventory Management
This paper addresses the capacitated periodic review inventory control problem, focusing on
a retailer managing multiple products with limited shared resources, such as storage or …
a retailer managing multiple products with limited shared resources, such as storage or …
Towards Measuring Sell Side Outcomes in Buy Side Marketplace Experiments using In-Experiment Bipartite Graph
V Pilkauskaitė, J Gamper, R Giniūnaitė… - arXiv preprint arXiv …, 2024 - arxiv.org
In this study, we evaluate causal inference estimators for online controlled bipartite graph
experiments in a real marketplace setting. Our novel contribution is constructing a bipartite …
experiments in a real marketplace setting. Our novel contribution is constructing a bipartite …