# S.S. Wilks Memorial Lecture

Princeton S. S. Wilks Memorial Lecture Series will feature one speaker per year.

This lecture series is funded by the S. S. Wilks Memorial Fund endowed in honor of the late Princeton Professor of Statistics Samuel Stanley Wilks.

#### Downsize Those Eigenvalues!

by David L. Donoho (Stanford University)

**Monday, April 17 at 4:45pm**

Computer Science 104

Abstract: Principal Components Analysis and Factor Analysis are used heavily across science and technology, in fields from population genetics to empirical finance. In recent years these methods were heavily used in 'Big Data' settings with very large datasets, often with as many variables/observables as observations/individuals/patients. 'Big Data' breaks the original justification for such methods. Tens of thousands of users are bound to be disappointed and frustrated with the results they actually get.

Thanks to recent advances in Random Matrix Theory, we can understand the disappointments that people are likely to face -- and propose corrected approaches. An important correction is to cut eigenvalues down to size, sometimes radically.

David L. Donoho is a Professor of Statistics and Anne T and Robert M Bass Professor in the Humanities and Sciences at Stanford University. He earned his AB in Statistics from Princeton and his PhD in Statistics from Harvard. He was co-founder of network management software company BigFix and has worked for Western Geophysical Company and Renaissance Technologies. He has published research in robust statistics, mathematical statistics, signal and image processing, harmonic analysis, scientific computing, and high dimensional geometry. He is a member of the US National Academy of Sciences as well as a foreign associate of the French Académie des Sciences. His work has been recognized by a MacArthur Fellow, the COPSS Presidents Award, John von Neumann Prize, Norbert Wiener Prize, Shaw Prize, among others. |