Active, non-parametric peak detection is considered. As a use case, acti...
This work studies the robust subspace tracking (ST) problem. Robust ST c...
Federated learning refers to a distributed learning scenario in which
us...
This work introduces the first simple and provably correct solution for
...
We study the related problems of subspace tracking in the presence of mi...
Principal Components Analysis (PCA) is one of the most widely used dimen...
Robust PCA (RPCA) is the problem of separating a given data matrix into ...
Principal Components Analysis (PCA) is one of the most widely used dimen...
This work obtains novel finite sample guarantees for Principal Component...
Dynamic robust PCA refers to the dynamic (time-varying) extension of the...
We study Principal Component Analysis (PCA) in a setting where a part of...