Abstract
The talk will first review the problem of robust subspace recovery, which seeks an underlying low-dimensional subspace in a data set that is possibly corrupted with outliers. The emphasis will be on surveying existing theoretical guarantees and tradeoffs. New results for adversarial outliers will also be mentioned. Following this, other related problems will be discussed, along with new results for one of these problems.