7 citations · 20 across the 12 of their papers we have counts for
13 papers
Conditional Predictive Inference for General Structured Data with Group Symmetries
Yichen Shen, Mengxin Yu
We study distribution-free predictive inference for data with group symmetries, aiming to establish near-conditional coverage guarantees beyond exchangeability for structured data.…
Covariate Assisted Entity Ranking with Sparse Intrinsic Scores
Jianqing Fan, Jikai Hou, Mengxin Yu
This paper addresses the item ranking problem with associate covariates, focusing on scenarios where the preference scores can not be fully explained by covariates, and the remaini…
Conformal causal inference for cluster randomized trials: model-robust inference without asymptotic approximations
Bingkai Wang, Fan Li, Mengxin Yu
Traditional statistical inference in cluster randomized trials typically invokes the asymptotic theory that requires the number of clusters to approach infinity. In this article, w…
SymmPI: Predictive Inference for Data with Group Symmetries
Edgar Dobriban, Mengxin Yu
Quantifying the uncertainty of predictions is a core problem in modern statistics. Methods for predictive inference have been developed under a variety of assumptions, often -- for…
Test-negative designs with various reasons for testing: statistical bias and solution
Mengxin Yu, Tom Hongyi Liu, Kendrick Qijun Li +5
Test-negative designs are widely used for post-market evaluation of vaccine effectiveness, particularly in cases when randomized trials are not feasible. Differing from classical t…
Spectral Ranking Inferences based on General Multiway Comparisons
Jianqing Fan, Zhipeng Lou, Weichen Wang +1
This paper studies the performance of the spectral method in the estimation and uncertainty quantification of the unobserved preference scores of compared entities in a general and…
Uncertainty Quantification of MLE for Entity Ranking with Covariates
Jianqing Fan, Jikai Hou, Mengxin Yu
This paper concerns with statistical estimation and inference for the ranking problems based on pairwise comparisons with additional covariate information such as the attributes of…
Robust High-dimensional Tuning Free Multiple Testing
Jianqing Fan, Zhipeng Lou, Mengxin Yu
A stylized feature of high-dimensional data is that many variables have heavy tails, and robust statistical inference is critical for valid large-scale statistical inference. Yet,…
Ranking Inferences Based on the Top Choice of Multiway Comparisons
Jianqing Fan, Zhipeng Lou, Weichen Wang +1
This paper considers ranking inference of items based on the observed data on the top choice among randomly selected items at each trial. This is a useful modification of t…
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments
Mengxin Yu, Zhuoran Yang, Jianqing Fan
We study offline reinforcement learning under a novel model called strategic MDP, which characterizes the strategic interactions between a principal and a sequence of myopic agents…
Are Latent Factor Regression and Sparse Regression Adequate?
Jianqing Fan, Zhipeng Lou, Mengxin Yu
We propose the Factor Augmented sparse linear Regression Model (FARM) that not only encompasses both the latent factor regression and sparse linear regression as special cases but…
Policy Optimization Using Semi-parametric Models for Dynamic Pricing
Jianqing Fan, Yongyi Guo, Mengxin Yu
In this paper, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one…
Understanding Implicit Regularization in Over-Parameterized Single Index Model
Jianqing Fan, Zhuoran Yang, Mengxin Yu
In this paper, we leverage over-parameterization to design regularization-free algorithms for the high-dimensional single index model and provide theoretical guarantees for the ind…