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20162022
most citedOnline Change Point Detection for Weighted and Directed Random Dot Product Graphs

8 citations · 12 across the 9 of their papers we have counts for

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eess.SP2022

Dual-based Online Learning of Dynamic Network Topologies

Seyed Saman Saboksayr, Gonzalo Mateos

We investigate online network topology identification from smooth nodal observations acquired in a streaming fashion. Different from non-adaptive batch solutions, our distinctive g…

eess.SP2021

Online Discriminative Graph Learning from Multi-Class Smooth Signals

Seyed Saman Saboksayr, Gonzalo Mateos, Mujdat Cetin

Graph signal processing (GSP) is a key tool for satisfying the growing demand for information processing over networks. However, the success of GSP in downstream learning and infer…

eess.SP20203 cited

Signal Processing on Directed Graphs

Antonio G. Marques, Santiago Segarra, Gonzalo Mateos

This paper provides an overview of the current landscape of signal processing (SP) on directed graphs (digraphs). Directionality is inherent to many real-world (information, transp…

eess.SP2020

Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information

Rasoul Shafipour, Gonzalo Mateos

We develop online graph learning algorithms from streaming network data. Our goal is to track the (possibly) time-varying network topology, and effect memory and computational savi…

eess.SP2018

Connecting the Dots: Identifying Network Structure via Graph Signal Processing

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

Network topology inference is a prominent problem in Network Science. Most graph signal processing (GSP) efforts to date assume that the underlying network is known, and then analy…

eess.SP2018

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals

Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo +1

We study the problem of sampling and reconstruction of bandlimited graph signals where the objective is to select a node subset of prescribed cardinality that ensures interpolation…