Event Date
Speaker: Zhenhua Lin (Presidential Young Professor, Statistics and Data Science, National University of Singapore)
Title: "Optimal One-pass Nonparametric Estimation Under Memory Constraint"
Abstract: For nonparametric regression in the streaming setting, where data constantly flow in and require real-time analysis, a main challenge is that data are cleared from the computer system once processed due to limited computer memory and storage. We tackle the challenge by proposing a novel one-pass estimator based on penalized orthogonal basis expansions and developing a general framework to study the interplay between statistical efficiency and memory consumption of estimators. We show that, the proposed estimator is statistically optimal under memory constraint, and has asymptotically minimal memory footprints among all one-pass estimators of the same estimation quality. Numerical studies demonstrate that the proposed one-pass estimator is nearly as efficient as its non-streaming counterpart that has access to all historical data.
Bio: Zhenhua Lin is currently Presidential Young Professor in Department of Statistics and Data Science, National University of Singapore. Prior to this he was a postdoctoral fellow in UC Davis and received his Ph.D. degree in statistics from University of Toronto, master's degrees in both statistics and computing science from Simon Fraser University, and bachelor's degree in computer science from Fudan University. His research primarily focuses on non-Euclidean/high-dimensional/functional data analysis and statistics under non-statistical constraints, with papers published in various statistical journals including The Annals of Statistics, Journal of the American Statistical Association, Biometrika, Biometrics and Journal of Computational and Graphical Statistics. He serves as an associate editor in the editorial board of Bernoulli Journal.
Webpage: https://blog.nus.edu.sg/zhenhua/
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Seminar Date/Time: Tuesday, November 15, 4:10pm, at MSB 1147 (Colloquium Room)
Refreshments: 3:30pm, MSB Courtyard (will move inside if it rains or is too cold)