1 citations · 1 across the 7 of their papers we have counts for
9 papers
Sample-Efficient Multiple Testing with Adaptive Data Collection
Zhanran Lin, Wanteng Ma, Zhimei Ren +1
This paper studies adaptive experimental design for multiple testing, where an experimenter sequentially chooses which hypothesis to sample. We propose the e-value-based posterior…
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…
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…
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…
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.…
Statistical Inference in Tensor Completion: Optimal Uncertainty Quantification and Statistical-to-Computational Gaps
Wanteng Ma, Dong Xia
This paper presents a simple yet efficient method for statistical inference of tensor linear forms using incomplete and noisy observations. Under the Tucker low-rank tensor model a…
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…
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…
Optimal Regularized Online Allocation by Adaptive Re-Solving
Wanteng Ma, Ying Cao, Danny H. K. Tsang +1
This paper introduces a dual-based algorithm framework for solving the regularized online resource allocation problems, which have potentially non-concave cumulative rewards, hard…