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07/25/2023
Gradient-Based Spectral Embeddings of Random Dot Product Graphs
The Random Dot Product Graph (RDPG) is a generative model for relational...
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05/27/2023
Explainable Brain Age Prediction using coVariance Neural Networks
In computational neuroscience, there has been an increased interest in d...
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05/02/2023
Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features
Graph convolutional networks (GCN) leverage topology-driven graph convol...
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03/20/2023
Fairness-Aware Graph Filter Design
Graphs are mathematical tools that can be used to represent complex real...
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11/07/2022
pyGSL: A Graph Structure Learning Toolkit
We introduce pyGSL, a Python library that provides efficient implementat...
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10/28/2022
Predicting Brain Age using Transferable coVariance Neural Networks
The deviation between chronological age and biological age is a well-rec...
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05/31/2022
coVariance Neural Networks
Graph neural networks (GNN) are an effective framework that exploit inte...
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05/19/2022
Learning Graph Structure from Convolutional Mixtures
Machine learning frameworks such as graph neural networks typically rely...
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01/26/2022
Online Change Point Detection for Weighted and Directed Random Dot Product Graphs
Given a sequence of random (directed and weighted) graphs, we address th...
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10/19/2021
Accelerated Graph Learning from Smooth Signals
We consider network topology identification subject to a signal smoothne...
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03/05/2021
Online Graph Learning under Smoothness Priors
The growing success of graph signal processing (GSP) approaches relies h...
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07/16/2020
Graph topology inference benchmarks for machine learning
Graphs are nowadays ubiquitous in the fields of signal processing and ma...
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03/12/2018
Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs
This paper deals with problem of blind identification of a graph filter ...
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10/31/2017
Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation
We study the problem of sampling a bandlimited graph signal in the prese...
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03/30/2015
Decentralized learning for wireless communications and networking
This chapter deals with decentralized learning algorithms for in-network...
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04/17/2014
Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors
Extracting latent low-dimensional structure from high-dimensional data i...
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01/31/2013
Rank regularization and Bayesian inference for tensor completion and extrapolation
A novel regularizer of the PARAFAC decomposition factors capturing the t...
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11/29/2012
Dynamic Network Cartography
Communication networks have evolved from specialized, research and tacti...
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04/30/2012
Recovery of Low-Rank Plus Compressed Sparse Matrices with Application to Unveiling Traffic Anomalies
Given the superposition of a low-rank matrix plus the product of a known...
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03/07/2012
In-network Sparsity-regularized Rank Minimization: Algorithms and Applications
Given a limited number of entries from the superposition of a low-rank m...
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11/08/2011
Robust PCA as Bilinear Decomposition with Outlier-Sparsity Regularization
Principal component analysis (PCA) is widely used for dimensionality red...
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04/04/2011