53 citations · 124 across the 6 of their papers we have counts for
7 papers
Robust Factor Analysis Parameter Estimation
Rui Zhou, Junyan Liu, Sandeep Kumar +1
This paper considers the problem of robustly estimating the parameters of a heavy-tailed multivariate distribution when the covariance matrix is known to have the structure of a lo…
Structured Graph Learning Via Laplacian Spectral Constraints
Sandeep Kumar, Jiaxi Ying, Jos'e Vin'icius de M. Cardoso +1
Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. It is well known that structured graph learning fro…
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
Sandeep Kumar, Ketan Rajawat, Daniel P. Palomar
In this two-part work, we propose an algorithmic framework for solving non-convex problems whose objective function is the sum of a number of smooth component functions plus a conv…
A Unified Framework for Structured Graph Learning via Spectral Constraints
Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso +1
Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior s…
Parameter Estimation of Heavy-Tailed AR Model with Missing Data via Stochastic EM
Junyan Liu, Sandeep Kumar, Daniel P. Palomar
The autoregressive (AR) model is a widely used model to understand time series data. Traditionally, the innovation noise of the AR is modeled as Gaussian. However, many time series…
Stochastic Multidimensional Scaling
Ketan Rajawat, Sandeep Kumar
Multidimensional scaling (MDS) is a popular dimensionality reduction techniques that has been widely used for network visualization and cooperative localization. However, the tradi…