Structured and Unstructured Outlier Identification for Robust PCA: A Non iterative, Parameter free Algorithm

by   Vishnu Menon, et al.
Indian Institute Of Technology, Madras

Robust PCA, the problem of PCA in the presence of outliers has been extensively investigated in the last few years. Here we focus on Robust PCA in the outlier model where each column of the data matrix is either an inlier or an outlier. Most of the existing methods for this model assumes either the knowledge of the dimension of the lower dimensional subspace or the fraction of outliers in the system. However in many applications knowledge of these parameters is not available. Motivated by this we propose a parameter free outlier identification method for robust PCA which a) does not require the knowledge of outlier fraction, b) does not require the knowledge of the dimension of the underlying subspace, c) is computationally simple and fast d) can handle structured and unstructured outliers. Further, analytical guarantees are derived for outlier identification and the performance of the algorithm is compared with the existing state of the art methods in both real and synthetic data for various outlier structures.


page 12

page 13


Fast, Parameter free Outlier Identification for Robust PCA

Robust PCA, the problem of PCA in the presence of outliers has been exte...

Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis

This paper presents a remarkably simple, yet powerful, algorithm termed ...

Stochastic and Private Nonconvex Outlier-Robust PCA

We develop theoretically guaranteed stochastic methods for outlier-robus...

Outlier Regularization for Vector Data and L21 Norm Robustness

In many real-world applications, data usually contain outliers. One popu...

Automatic identification of outliers in Hubble Space Telescope galaxy images

Rare extragalactic objects can carry substantial information about the p...

Low Rank Approximation in the Presence of Outliers

We consider the problem of principal component analysis (PCA) in the pre...

Re-weighting and 1-Point RANSAC-Based PnP Solution to Handle Outliers

The ability to handle outliers is essential for performing the perspecti...

Please sign up or login with your details

Forgot password? Click here to reset