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20132026
most citedConnecting the Dots: Identifying Network Structure via Graph Signal Processing

385 citations · 2k across the 117 of their papers we have counts for

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Showing cs.ITShow all

5 papers · 1 filter

cs.IT2023★ 35 cited

A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks

Qing An, Santiago Segarra, Chris Dick +2

The large number of antennas in massive MIMO systems allows the base station to communicate with multiple users at the same time and frequency resource with multi-user beamforming.…

cs.IT2021

ML-aided power allocation for Tactical MIMO

Arindam Chowdhury, Gunjan Verma, Chirag Rao +2

We study the problem of optimal power allocation in single-hop multi-antenna ad-hoc wireless networks. A standard technique to solve this problem involves optimizing a tri-convex f…

cs.IT2017★ 5 cited

The Dual Graph Shift Operator: Identifying the Support of the Frequency Domain

Geert Leus, Santiago Segarra, Alejandro Ribeiro +1

Contemporary data is often supported by an irregular structure, which can be conveniently captured by a graph. Accounting for this graph support is crucial to analyze the data, lea…

cs.IT2016★ 82 cited

Blind Identification of Graph Filters

Santiago Segarra, Gonzalo Mateos, Antonio G. Marques +1

Network processes are often represented as signals defined on the vertices of a graph. To untangle the latent structure of such signals, one can view them as outputs of linear grap…

cs.IT2015★ 18 cited

Distributed Linear Network Operators using Graph Filters

Santiago Segarra, Antonio G. Marques, Alejandro Ribeiro

We study the design of graph filters to implement arbitrary linear transformations between graph signals. Graph filters can be represented by matrix polynomials of the graph-shift…