On Mathematics of Data

• Activity Number: 288
• Type: Topic Contributed
• Date/Time: Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistical Computing
• Author(s): Yuan Yao*+
• Companies: Peking University
• Keywords: data analysis ; algebraic topology ; discrete geometry ; statististical computing

Abstract

Over the last two decades, the world has witnessed an enormous growth in data sets that are complex, high-dimensional, and massive. This is in part an inevitable consequence of technological advancement. Among other factors, more sophisticated instruments and sensoring devices (from gene sequencers to camera phones), new human activities in the web-enabled world have led to ever-more complicated data being created and collected on a never-before scale. Traditional techniques for analyzing data have become inadequate and it calls upon a wider scope of collaborations among computer scientists, statisticians and mathematicians, the former two groups have fostered the growth of computational statistics. In this talk, we will discuss how mathematics created for largely intellectual reasons (algebraic topology, differential geometry, harmonic analysis, etc) or for completely different purposes (e.g. processing communication signals or understanding human intelligence), could nonetheless provide powerful new tools for analyzing these modern data sets. In particular we will focus on some novel schemes arising from traditional topology and geometry in modern data analysis.