Hi! My name is Luofeng Liao (廖烙锋 in Chinese) and I am a second-year phd student in the IEOR Department at Columbia.
My research interests are machine learning methods for causal inference and econometrics, learning and inference in market design, and adversarial optimization.
Currently, I’m working with Prof. Christian Kroer on statistical inference theory for equilibrium in auction markets, a theory that is useful for internet advertising business. Prior to Columbia, I received my bachelor’s degree in computer science in Fudan University in China and a master’s degree in statistics in University of Chicago. In UChicago, I used to work with Prof. Mladen Kolar and Prof. Zhaoran Wang. In Fudan I was advised by Prof. Ke Wei.
- preprintInterference Among First-Price Pacing Equilibria: A Bias and Variance Analysis2024
- preprintBootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium2024
- AAAI2024Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees2023
- ICML2023Statistical Inference and A/B Testing for First-Price Pacing Equilibria2023
- ICLR2023Statistical Inference for Fisher Market Equilibrium2022
- NeurIPS2022Nonstationary Dual Averaging and Online Fair Allocation2022
- MLJLocal AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax ProblemsMachine Learning Journal 2022
- preprintInstrumental Variable Value Iteration for Causal Offline Reinforcement Learning2021
- NeurIPS2020Provably efficient neural estimation of structural equation model: An adversarial approach2020