10 citations · 17 across the 5 of their papers we have counts for
7 papers
From Common Information to Canonical Correlation Analysis and Beyond: Bridging Information Theory, Signal Processing, and Machine Learning
Paris A. Karakasis, Walid Saad
Many problems in signal processing, machine learning, and neuroimaging provide several jointly observed measurements of one process, each mixing a component common to all of them w…
Latent Semantic State Estimation for Reliable Swarming of UAVs under Intermittent Connectivity
Paris A. Karakasis, Walid Saad
Cooperative multi-unmanned aerial vehicle (UAV) reconnaissance is often hindered by intermittent air-to-air communications where link dropouts lead to uncoordinated exploration and…
Penalizing Localized Dirichlet Energies in Low Rank Tensor Products
Paris A. Karakasis, Nicholas D. Sidiropoulos
We study low-rank tensor-product B-spline (TPBS) models for regression tasks and investigate Dirichlet energy as a measure of smoothness. We show that TPBS models admit a closed-fo…
Subspace Clustering of Subspaces: Unifying Canonical Correlation Analysis and Subspace Clustering
Paris A. Karakasis, Nicholas D. Sidiropoulos
We introduce a novel framework for clustering a collection of tall matrices based on their column spaces, a problem we term Subspace Clustering of Subspaces (SCoS). Unlike traditio…
Revisiting Deep Generalized Canonical Correlation Analysis
Paris A. Karakasis, Nicholas D. Sidiropoulos
Canonical correlation analysis (CCA) is a classic statistical method for discovering latent co-variation that underpins two or more observed random vectors. Several extensions and…
Multisubject Task-Related fMRI Data Processing via a Two-Stage Generalized Canonical Correlation Analysis
Paris A. Karakasis, Athanasios P. Liavas, Nicholas D. Sidiropoulos +2
Functional magnetic resonance imaging (fMRI) is one of the most popular methods for studying the human brain. Task-related fMRI data processing aims to determine which brain areas…
Minimizing low-rank models of high-order tensors: Hardness, span, tight relaxation, and applications
Nicholas D. Sidiropoulos, Paris Karakasis, Aritra Konar
We consider the problem of finding the smallest or largest entry of a tensor of order N that is specified via its rank decomposition. Stated in a different way, we are given N sets…