Systems | Information | Learning | Optimization
 

New Perspectives in Robust, High-dimensional Statistics

Video: https://vimeo.com/159423831 Robust statistics provides a powerful framework for quantifying the behavior of estimators when data are observed subject to imperfections that deviate from standard modeling assumptions. In this talk, we highlight recent work involving statistical theory for robust estimators in high dimensions, with applications to compressed sensing and graphical …

Learning with systematic corruptions: Regression-based methods with applications to MRI and graph estimation

We will discuss a line of recent work on methods for statistical inference in high dimensions. In many real-world applications, samples are not collected cleanly and may be observed subject to systematic corruptions such as missing data and additive noise. We describe how Lasso-based linear regression may be corrected to …