Details:
Speaker: Peng Zeng
Title: Statistical Analysis and Modeling for High-Dimensional Data
Abstract: High-dimensional data become popular nowadays, for example, biological sequencing data, image data, consumer transaction data, social network data, etc. Classic statistical models and methods are inefficient and sometimes infeasible for analyzing these data. There is a great demand to develop novel statistical models and methods. In this talk, I will first review some challenges caused by high-dimensionality, and then focus on several research areas in high-dimensional data analysis, namely, linear regression with regularization, single-index models, and dimension reduction. I will discuss the work I have done in these areas, as well as some directions I will pursue in the near future.
Please note for this colloquium the room is Parker 249
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