13 citations · 24 across the 10 of their papers we have counts for
11 papers
Tight Non-asymptotic Inference via Sub-Gaussian Intrinsic Moment Norm
Huiming Zhang, Haoyu Wei, Guang Cheng
In non-asymptotic learning, variance-type parameters of sub-Gaussian distributions are of paramount importance. However, directly estimating these parameters using the empirical mo…
Multiplier Bootstrap-based Exploration
Runzhe Wan, Haoyu Wei, Branislav Kveton +1
Despite the great interest in the bandit problem, designing efficient algorithms for complex models remains challenging, as there is typically no analytical way to quantify uncerta…
Concentration inequalities of MLE and robust MLE
Xiaowei Yang, Xinqiao Liu, Haoyu Wei
The Maximum Likelihood Estimator (MLE) serves an important role in statistics and machine learning. In this article, for i.i.d. variables, we obtain constant-specified and sharp co…
High-dimensional Inference and FDR Control for Simulated Markov Random Fields
Haoyu Wei, Xiaoyu Lei, Yixin Han +1
Identifying important features linked to a response variable is a fundamental task in various scientific domains. This article explores statistical inference for simulated Markov r…
Asymptotic in a class of network models with an increasing sub-Gamma degree sequence
Jing Luo, Haoyu Wei, Xiaoyu Lei +1
For the differential privacy under the sub-Gamma noise, we derive the asymptotic properties of a class of network models with binary values with a general link function. In this pa…
Nonparametric Tests of Conditional Independence for Time Series
Xiaojun Song, Haoyu Wei
We propose consistent nonparametric tests of conditional independence for time series data. Our methods are motivated from the difference between joint conditional cumulative distr…
Data-driven Smooth Tests for Normality in ANOVA When the Number of Groups is Large
Peiwen Jia, Xiaojun Song, Haoyu Wei
The normality assumption for random errors is fundamental in the analysis of variance (ANOVA) models. However, it is rarely subjected to formal testing in practice, and theoretical…
Heterogeneous Overdispersed Count Data Regressions via Double Penalized Estimations
Shaomin Li, Haoyu Wei, Xiaoyu Lei
This paper studies the non-asymptotic merits of the double -regularized for heterogeneous overdispersed count data via negative binomial regressions. Under the restricted e…
Sharper Sub-Weibull Concentrations
Huiming Zhang, Haoyu Wei
Constant-specified and exponential concentration inequalities play an essential role in the finite-sample theory of machine learning and high-dimensional statistics area. We obtain…
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network
Haoyu Wei, Florian Schiffers, Tobias Würfl +4
Computed tomography is widely used to examine internal structures in a non-destructive manner. To obtain high-quality reconstructions, one typically has to acquire a densely sample…
Sparse Density Estimation with Measurement Errors
Xiaowei Yang, Huiming Zhang, Haoyu Wei +1
This paper aims to build an estimate of an unknown density of the data with measurement error as a linear combination of functions from a dictionary. Inspired by the penalization a…