225 citations · 752 across the 41 of their papers we have counts for
5 papers · 1 filter
Two new algorithms for maximum likelihood estimation of sparse covariance matrices with applications to graphical modeling
Ghania Fatima, Prabhu Babu, Petre Stoica
In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state of-the-art methods, wh…
Pearson-Matthews correlation coefficients for binary and multinary classification and hypothesis testing
Petre Stoica, Prabhu Babu
The Pearson-Matthews correlation coefficient (usually abbreviated MCC) is considered to be one of the most useful metrics for the performance of a binary classification or hypothes…
Fair principal component analysis (PCA): minorization-maximization algorithms for Fair PCA, Fair Robust PCA and Fair Sparse PCA
Prabhu Babu, Petre Stoica
In this paper we propose a new iterative algorithm to solve the fair PCA (FPCA) problem. We start with the max-min fair PCA formulation originally proposed in [1] and derive a simp…
Low-rank covariance matrix estimation for factor analysis in anisotropic noise: application to array processing and portfolio selection
Petre Stoica, Prabhu Babu
Factor analysis (FA) or principal component analysis (PCA) models the covariance matrix of the observed data as R = SS' + Σ, where SS' is the low-rank covariance matrix of the fact…
Off-Policy Evaluation with Out-of-Sample Guarantees
Sofia Ek, Dave Zachariah, Fredrik D. Johansson +1
We consider the problem of evaluating the performance of a decision policy using past observational data. The outcome of a policy is measured in terms of a loss (aka. disutility or…