activity
20242026
collaborators

7 papers

stat.ME2026

Multiple Testing of Linear Forms for Noisy Matrix Completion

Wanteng Ma, Lilun Du, Dong Xia +1

Many important tasks of large-scale recommender systems can be naturally cast as testing multiple linear forms for noisy matrix completion. These problems, however, present unique…

stat.ME2026

Conformal Network Link Prediction with False Discovery Rate Control under Unstructured Missingness

Wenqin Du, Wanteng Ma, Dong Xia +2

We propose a new method for predicting multiple missing links in partially observed networks while controlling the false discovery rate (FDR), a largely unresolved challenge in net…

math.ST2025

Nonparametric Bandits with Single-Index Rewards: Optimality and Adaptivity

Wanteng Ma, T. Tony Cai

Contextual bandits are a central framework for sequential decision-making, with applications ranging from recommendation systems to clinical trials. While nonparametric methods can…

stat.ME2025

Statistical Inference for Matching Decisions via Matrix Completion under Dependent Missingness

Congyuan Duan, Wanteng Ma, Dong Xia +1

This paper studies decision-making and statistical inference for two-sided matching markets via matrix completion. In contrast to the independent sampling assumed in classical matr…

cs.LG2025

High-dimensional Linear Bandits with Knapsacks

Wanteng Ma, Dong Xia, Jiashuo Jiang

We investigate the contextual bandits with knapsack (CBwK) problem in a high-dimensional linear setting, where the feature dimension can be very large. Our goal is to harness spars…

cs.LG2025

Regret Minimization and Statistical Inference in Online Decision Making with High-dimensional Covariates

Congyuan Duan, Wanteng Ma, Jiashuo Jiang +1

This paper investigates regret minimization, statistical inference, and their interplay in high-dimensional online decision-making based on the sparse linear context bandit model.…