179 citations · 254 across the 7 of their papers we have counts for
10 papers
Limit Theory for Online Expectile Estimation under Short and Long Range Dependence
Younghun Lee, Jake Zummo, Wei Biao Wu
Expectiles are tail-sensitive distributional summaries with important applications in financial risk measurement and forecasting, yet statistical theory for their online estimation…
Gaussian Limits for SGD Without Stationary Moments
Xiaoli Li, Wei Biao Wu
Temporal dependence can separate the Gaussian approximation of stochastic gradient descent from its stationary moments. For unmodified least-squares SGD, we construct a design with…
Bandable Cumulant Tensors: Optimal Estimation and Applications in Non-Gaussian Data Modeling
Runshi Tang, Anru R. Zhang, Yuefeng Han +1
Higher-order cumulants capture the non-Gaussian dependence that covariance misses, but they are hard to use in high dimensions. An order- cumulant tensor has entries, and…
Online simultaneous inference for quantiles via smoothed stochastic gradient descent
Likai Chen, Georg Keilbar, Wei Biao Wu
This paper considers the estimation of quantiles via a smoothed version of the stochastic gradient descent (SGD) algorithm. By smoothing the score function with a bandwidth tied to…
Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM
Jiaqi Li, Likai Chen, Weining Wang +1
We propose an inference method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. Our method aggregates moving su…
Sequential Detection of Common Change in High-dimensional Data Stream
Yanhong Wu, Wei Biao Wu
After obtaining an accurate approximation for , we first consider the optimal design of weight parameter for a multivariate EWMA chart that minimizes the stationary average…
Testing and estimation of clustered signals
Hongyuan Cao, Wei Biao Wu
We propose a change-point detection method for large scale multiple testing problems with data having clustered signals. Unlike the classic change-point setup, the signals can vary…
Online Covariance Matrix Estimation in Stochastic Gradient Descent
Wanrong Zhu, Xi Chen, Wei Biao Wu
The stochastic gradient descent (SGD) algorithm is widely used for parameter estimation, especially for huge data sets and online learning. While this recursive algorithm is popula…
Komlós-Major-Tusnády approximation under dependence
István Berkes, Weidong Liu, Wei Biao Wu
The celebrated results of Komlós, Major and Tusnády [Z. Wahrsch. Verw. Gebiete 32 (1975) 111-131; Z. Wahrsch. Verw. Gebiete 34 (1976) 33-58] give optimal Wiener approximation for t…
Strong invariance principles for dependent random variables
Wei Biao Wu
We establish strong invariance principles for sums of stationary and ergodic processes with nearly optimal bounds. Applications to linear and some nonlinear processes are discussed…