An Overview of Robust Subspace Recovery

Understand

This paper will serve as an introduction to the body of work on robust subspace recovery.

• Robust subspace recovery involves finding an underlying low-dimensional subspace in a dataset that is possibly corrupted with outliers.
• While this problem is easy to state, it has been difficult to develop optimal algorithms due to its underlying nonconvexity.
• This work emphasizes advantages and disadvantages of proposed approaches and unsolved problems in the area.