Random Graphs And The Strong Convergence Of Bootstrap Means. - Sándor Csörgo; Wei Biao Wu (Comb. Probab. Comput., 2000)

Exact distribution of edge-preserving MAP estimators for linear signal models with Gaussian measurement noise. - Jeffrey A. Fessler; Hakan Erdogan; Wei Biao Wu (IEEE Trans. Image Process., 2000)

Analysis on Markov modeling of cellular packet transmission. - Danlu Zhang; Wei Biao Wu; Kimberly M. Wasserman (WCNC, 2002)

General methodology 2: an efficient method for simulating fractional stable motion. - Wei Biao Wu; George Michailidis; Danlu Zhang (WSC, 2002)

The performance of difference coding for sets and relational tables. - Wei Biao Wu; Chinya V. Ravishankar (J. ACM, 2003)

On the clustering of independent uniform random variables. - Sándor Csörgo; Wei Biao Wu (Random Struct. Algorithms, 2004)

Simulating Sample Paths of Linear Fractional Stable Motion. - Wei Biao Wu; George Michailidis; Danlu Zhang (IEEE Trans. Inf. Theory, 2004)

Best-Effort Patching for Multicast True VoD Service. - Huadong Ma; Kang G. Shin; Wei Biao Wu (Multim. Tools Appl., 2005)

Robust prediction of network traffic using quantile regression models. - Wei Biao Wu; Zhiwei Xu 001; Yu Wang (IRI, 2006)

Long-term prediction intervals of time series. - Zhou Zhou; Zhiwei Xu 001; Wei Biao Wu (IEEE Trans. Inf. Theory, 2010)

A Single-Pass Algorithm for Spectrum Estimation With Fast Convergence. - Han Xiao 007; Wei Biao Wu (IEEE Trans. Inf. Theory, 2011)

Testing for Parallelism Among Trends in Multiple Time Series. - David Degras; Zhiwei Xu 001; Ting Zhang; Wei Biao Wu (IEEE Trans. Signal Process., 2012)

Recursive Nonparametric Estimation for Time Series. - Yinxiao Huang; Xiaohong Chen 006; Wei Biao Wu (IEEE Trans. Inf. Theory, 2014)

In-band wormhole detection in wireless ad hoc networks using change point detection method. - Maggie X. Cheng; Yi Ling; Wei Biao Wu (ICC, 2016)

A model-free localization method for sensor networks with sparse anchors. - Maggie X. Cheng; Wei Biao Wu (ICC, 2016)

Data Analytics for Fault Localization in Complex Networks. - Maggie X. Cheng; Wei Biao Wu (IEEE Internet Things J., 2016)

A Hypothesis Testing Approach for Topology Error Detection in Power Grids. - Wei Biao Wu; Maggie X. Cheng; Bei Gou (IEEE Internet Things J., 2016)

Regularized Estimation of Linear Functionals of Precision Matrices for High-Dimensional Time Series. - Xiaohui Chen; Mengyu Xu; Wei Biao Wu (IEEE Trans. Signal Process., 2016)

Time Series Analysis for Jamming Attack Detection in Wireless Networks. - Maggie X. Cheng; Yi Ling; Wei Biao Wu (GLOBECOM, 2017)

Concentration inequalities for empirical processes of linear time series. - Likai Chen; Wei Biao Wu (J. Mach. Learn. Res., 2017)

MAC Layer Misbehavior Detection Using Time Series Analysis. - Maggie X. Cheng; Yi Ling; Wei Biao Wu (ICC, 2018)

Asymptotic Theory for Estimators of High-Order Statistics of Stationary Processes. - Danna Zhang; Wei Biao Wu (IEEE Trans. Inf. Theory, 2018)

A Fully Online Approach for Covariance Matrices Estimation of Stochastic Gradient Descent Solutions. - Wanrong Zhu; Xi Chen; Wei Biao Wu (CoRR, 2020)

Estimation of Dynamic Networks for High-Dimensional Nonstationary Time Series. - Mengyu Xu; Xiaohui Chen; Wei Biao Wu (Entropy, 2020)

Central limit theorems for nearly long range dependent subordinated linear processes. - Martin Wendler; Wei Biao Wu (J. Appl. Probab., 2020)

Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach. - Ayman Moawad; Ehsan Islam; Namdoo Kim; Ram Vijayagopal; Aymeric Rousseau; Wei Biao Wu (IEEE Trans. Artif. Intell., 2021)

Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent. - Wanrong Zhu; Zhipeng Lou; Wei Biao Wu (J. Mach. Learn. Res., 2022)

Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality. - Ziyang Wei; Wanrong Zhu; Wei Biao Wu (CoRR, 2023)

Recursive Quantile Estimation: Non-Asymptotic Confidence Bounds. - Likai Chen; Georg Keilbar; Wei Biao Wu (J. Mach. Learn. Res., 2023)

High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization. - Wanrong Zhu; Zhipeng Lou; Ziyang Wei; Wei Biao Wu (CoRR, 2024)

Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models. - Jiaqi Li; Johannes Schmidt-Hieber; Wei Biao Wu (CoRR, 2024)

Online Inference for Quantiles by Constant Learning-Rate Stochastic Gradient Descent. - Ziyang Wei; Jiaqi Li; Likai Chen; Wei Biao Wu (CoRR, 2025)

Sharp Gaussian approximations for Decentralized Federated Learning. - Soham Bonnerjee; Sayar Karmakar; Wei Biao Wu (CoRR, 2025)

Smoothed SGD for quantiles: Bahadur representation and Gaussian approximation. - Likai Chen; Georg Keilbar; Wei Biao Wu (CoRR, 2025)

Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling. - Xinchen Du; Wanrong Zhu; Wei Biao Wu; Sen Na (CoRR, 2025)