Recent Advances in Algorithmic High-Dimensional Robust Statistics

Neyman Seminar
Feb 21, 2018 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
Fitting a model to a collection of observations is one of the quintessential problems in machine learning. Since any model is only approximately valid, an estimator that is useful in practice must also be robust in the presence of model misspecification. It turns out that there is a striking tension between robustness and computational efficiency. Even for the most basic high-dimensional tasks,...
Ilias Diakonikolas, USC