activity
20222026
most citedTime Series Generation with Masked Autoencoder

7 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Adapting to noise tails in private linear regression

Jinyuan Chang, Lin Yang, Mengyue Zha +1

While the traditional goal of statistics is to infer population parameters, modern practice increasingly demands protection of individual privacy. One way to address this need is t…

stat.ML2024★ 1 cited

Near-Optimal differentially private low-rank trace regression with guaranteed private initialization

Mengyue Zha

We study differentially private (DP) estimation of a rank- matrix under the trace regression model with Gaussian measurement matrices. Theoret…

math.ST2024★ 1 cited

Optimal Differentially Private PCA and Estimation for Spiked Covariance Matrices

T. Tony Cai, Dong Xia, Mengyue Zha

Estimating a covariance matrix and its associated principal components is a fundamental problem in contemporary statistics. While optimal estimation procedures have been developed…

cs.LG2022

IDEA: Interpretable Dynamic Ensemble Architecture for Time Series Prediction

Mengyue Zha, Kani Chen, Tong Zhang

We enhance the accuracy and generalization of univariate time series point prediction by an explainable ensemble on the fly. We propose an Interpretable Dynamic Ensemble Architectu…

cs.LG2022★ 7 cited

Time Series Generation with Masked Autoencoder

Mengyue Zha, SiuTim Wong, Mengqi Liu +2

This paper shows that masked autoencoder with extrapolator (ExtraMAE) is a scalable self-supervised model for time series generation. ExtraMAE randomly masks some patches of the or…