3 citations · 5 across the 3 of their papers we have counts for
6 papers
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin, Andreas Loukas, Pierre Vandergheynst
Spectral clustering is a widely studied problem, yet its complexity is prohibitive for dynamic graphs of even modest size. We claim that it is possible to reuse information of past…
Towards Communication-Aware Robust Topologies
Chen Avin, Alexandr Hercules, Andreas Loukas +1
We currently witness the emergence of interesting new network topologies optimized towards the traffic matrices they serve, such as demand-aware datacenter interconnects (e.g., Pro…
A Time-Vertex Signal Processing Framework
Francesco Grassi, Andreas Loukas, Nathanaël Perraudin +1
An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related…
How close are the eigenvectors and eigenvalues of the sample and actual covariance matrices?
Andreas Loukas
How many samples are sufficient to guarantee that the eigenvectors and eigenvalues of the sample covariance matrix are close to those of the actual covariance matrix? For a wide fa…
Predicting the evolution of stationary graph signals
Andreas Loukas, Nathanael Perraudin
An emerging way of tackling the dimensionality issues arising in the modeling of a multivariate process is to assume that the inherent data structure can be captured by a graph. Ne…
Towards stationary time-vertex signal processing
Nathanael Perraudin, Andreas Loukas, Francesco Grassi +1
Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor netw…