Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2020)

Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Zhaoran Wang 001; Mladen Kolar (CoRR, 2020)

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. - Luofeng Liao; Zuyue Fu; Zhuoran Yang; Mladen Kolar; Zhaoran Wang 001 (CoRR, 2021)

Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax Problems. - Luofeng Liao; Li Shen 008; Jia Duan; Mladen Kolar; Dacheng Tao (CoRR, 2021)

Nonstationary Dual Averaging and Online Fair Allocation. - Luofeng Liao; Yuan Gao; Christian Kroer (NeurIPS, 2022)

Statistical Inference for Fisher Market Equilibrium. - Luofeng Liao; Yuan Gao; Christian Kroer (ICLR, 2023)

Statistical Inference and A/B Testing for First-Price Pacing Equilibria. - Luofeng Liao; Christian Kroer (ICML, 2023)

Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees. - Zongjun Yang; Luofeng Liao; Christian Kroer (AAAI, 2024)

Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium. - Luofeng Liao; Christian Kroer (ICML, 2024)

Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions. - Luofeng Liao; Christian Kroer (CoRR, 2024)

Online Fair Allocation with Best-of-Many-Worlds Guarantees. - Zongjun Yang; Luofeng Liao; Yuan Gao; Christian Kroer (CoRR, 2024)

Local AdaGrad-type algorithm for stochastic convex-concave optimization. - Luofeng Liao; Li Shen 008; Jia Duan; Mladen Kolar; Dacheng Tao (Mach. Learn., 2024)

Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis. - Luofeng Liao; Christian Kroer; Sergei Leonenkov; Okke Schrijvers; Liang Shi; Nicolás Stier Moses; Congshan Zhang (ICLR, 2025)