171 citations · 321 across the 4 of their papers we have counts for
8 papers
Minimum Mean-Squared-Error Autocorrelation Processing in Coprime Arrays
Dimitris G. Chachlakis, Tongdi Zhou, Fauzia Ahmad +1
Coprime arrays enable Direction-of-Arrival (DoA) estimation of an increased number of sources. To that end, the receiver estimates the autocorrelation matrix of a larger virtual un…
Structured Autocorrelation Matrix Estimation for Coprime Arrays
Dimitris G. Chachlakis, Panos P. Markopoulos
A coprime array receiver processes a collection of received-signal snapshots to estimate the autocorrelation matrix of a larger (virtual) uniform linear array, known as coarray. By…
L1-norm Tucker Tensor Decomposition
Dimitris G. Chachlakis, Ashley Prater-Bennette, Panos P. Markopoulos
Tucker decomposition is a common method for the analysis of multi-way/tensor data. Standard Tucker has been shown to be sensitive against heavy corruptions, due to its L2-norm-base…
The Exact Solution to Rank-1 L1-norm TUCKER2 Decomposition
Panos P. Markopoulos, Dimitris G. Chachlakis, Evangelos E. Papalexakis
We study rank-1 {L1-norm-based TUCKER2} (L1-TUCKER2) decomposition of 3-way tensors, treated as a collection of matrices that are to be jointly decomposed. Our con…
Efficient L1-Norm Principal-Component Analysis via Bit Flipping
Panos P. Markopoulos, Sandipan Kundu, Shubham Chamadia +1
It was shown recently that the L1-norm principal components (L1-PCs) of a real-valued data matrix ( data samples of dimensions) ca…
Uniformly most powerful unbiased test for conditional independence in Gaussian graphical model
Koldanov Petr, Koldanov Alexander, Kalyagin Valeriy +1
Model selection for Gaussian concentration graph is based on multiple testing of pairwise conditional independence. In practical applications partial correlation tests are widely u…
Optimal Algorithms for -subspace Signal Processing
Panos P. Markopoulos, George N. Karystinos, Dimitris A. Pados
We describe ways to define and calculate -norm signal subspaces which are less sensitive to outlying data than -calculated subspaces. We start with the computation of the…
Some Options for L1-Subspace Signal Processing
Panos P. Markopoulos, George N. Karystinos, Dimitris A. Pados
We describe ways to define and calculate -norm signal subspaces which are less sensitive to outlying data than -calculated subspaces. We focus on the computation of the $…