4 papers
Provable Low Rank Phase Retrieval
Seyedehsara Nayer, Praneeth Narayanamurthy, Namrata Vaswani
We study the Low Rank Phase Retrieval (LRPR) problem defined as follows: recover an matrix of rank from a different and independent set of phaseless (mag…
Provable Subspace Tracking from Missing Data and Matrix Completion
Praneeth Narayanamurthy, Vahid Daneshpajooh, Namrata Vaswani
We study the problem of subspace tracking in the presence of missing data (ST-miss). In recent work, we studied a related problem called robust ST. In this work, we show that a sim…
Static and Dynamic Robust PCA and Matrix Completion: A Review
Namrata Vaswani, Praneeth Narayanamurthy
Principal Components Analysis (PCA) is one of the most widely used dimension reduction techniques. Robust PCA (RPCA) refers to the problem of PCA when the data may be corrupted by…
Finite Sample Guarantees for PCA in Non-Isotropic and Data-Dependent Noise
Namrata Vaswani, Praneeth Narayanamurthy
This work obtains novel finite sample guarantees for Principal Component Analysis (PCA). These hold even when the corrupting noise is non-isotropic, and a part (or all of it) is da…