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03/13/2023
Tight Non-asymptotic Inference via Sub-Gaussian Intrinsic Moment Norm
In non-asymptotic statistical inferences, variance-type parameters of su...
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12/28/2022
Distribution Estimation of Contaminated Data via DNN-based MoM-GANs
This paper studies the distribution estimation of contaminated data by t...
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02/11/2022
Inference and FDR Control for Simulated Ising Models in High-dimension
This paper studies the consistency and statistical inference of simulate...
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01/10/2022
Non-Asymptotic Guarantees for Robust Statistical Learning under (1+ε)-th Moment Assumption
There has been a surge of interest in developing robust estimators for m...
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10/22/2021
Adaptive Fusion Affinity Graph with Noise-free Online Low-rank Representation for Natural Image Segmentation
Affinity graph-based segmentation methods have become a major trend in c...
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05/02/2021
Directional FDR Control for Sub-Gaussian Sparse GLMs
High-dimensional sparse generalized linear models (GLMs) have emerged in...
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02/04/2021
Sharper Sub-Weibull Concentrations: Non-asymptotic Bai-Yin Theorem
Arising in high-dimensional probability, non-asymptotic concentration in...
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01/31/2021
A Unified Light Framework for Real-time Fault Detection of Freight Train Images
Real-time fault detection for freight trains plays a vital role in guara...
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11/04/2020
Concentration Inequalities for Statistical Inference
This paper gives a review of concentration inequalities which are widely...
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09/10/2020
Non-asymptotic Optimal Prediction Error for RKHS-based Partially Functional Linear Models
Under the framework of reproducing kernel Hilbert space (RKHS), we consi...
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08/08/2020
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization
In this paper, we present a novel framework that can achieve multimodal ...
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06/11/2020
Weighted Lasso Estimates for Sparse Logistic Regression: Non-asymptotic Properties with Measurement Error
When we are interested in high-dimensional system and focus on classific...
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05/21/2020
Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data
Nonuniform subsampling methods are effective to reduce computational bur...
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02/28/2020
Asymptotic Theory for Differentially Private Generalized β-models with Parameters Increasing
Modelling edge weights play a crucial role in the analysis of network da...
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11/14/2019
Sparse Density Estimation with Measurement Errors
This paper aims to build an estimate of an unknown density of the data w...
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09/25/2018
Some Characterizations and Properties of COM-Poisson Random Variables
This paper introduces some new characterizations of COM-Poisson random v...
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06/18/2018
Optimal Subsampling Algorithms for Big Data Generalized Linear Models
To fast approximate the maximum likelihood estimator with massive data, ...
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01/26/2018
A note on "MLE in logistic regression with a diverging dimension"
This short note is to point the reader to notice that the proof of high ...
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12/09/2017