7 papers
The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub +3
Data-driven stochastic optimization is ubiquitous in machine learning and operational decision-making problems. Sample average approximation (SAA) and model-based approaches such a…
Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
Luofeng Liao, Christian Kroer
The linear Fisher market (LFM) is a basic equilibrium model from economics, which also has applications in fair and efficient resource allocation. First-price pacing equilibrium (F…
Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions
Luofeng Liao, Christian Kroer
We initiate the study of statistical inference and A/B testing for two market equilibrium models: linear Fisher market (LFM) equilibrium and first-price pacing equilibrium (FPPE).…
Statistical Inference for Fisher Market Equilibrium
Luofeng Liao, Yuan Gao, Christian Kroer
Statistical inference under market equilibrium effects has attracted increasing attention recently. In this paper we focus on the specific case of linear Fisher markets. They have…
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Luofeng Liao, Christian Kroer, Sergei Leonenkov +4
Online A/B testing is widely used in the internet industry to inform decisions on new feature roll-outs. For online marketplaces (such as advertising markets), standard approaches…
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
Luofeng Liao, Zuyue Fu, Zhuoran Yang +3
In offline reinforcement learning (RL) an optimal policy is learned solely from a priori collected observational data. However, in observational data, actions are often confounded…