Gonzalo Mateos

According to our database1, Gonzalo Mateos authored at least 79 papers between 2008 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2020
Signal Processing on Directed Graphs: The Role of Edge Directionality When Processing and Learning From Network Data.
IEEE Signal Process. Mag., 2020

Rethinking sketching as sampling: A graph signal processing approach.
Signal Process., 2020

Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information.
Algorithms, 2020

Graph Topology Inference Benchmarks for Machine Learning.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Supervised Graph Representation Learning for Modeling the Relationship between Structural and Functional Brain Connectivity.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Directed Graph Fourier Transform With Spread Frequency Components.
IEEE Trans. Signal Process., 2019

Connecting the Dots: Identifying Network Structure via Graph Signal Processing.
IEEE Signal Process. Mag., 2019

A Windowed Digraph Fourier Transform.
Proceedings of the IEEE International Conference on Acoustics, 2019

Identifying Structural Brain Networks from Functional Connectivity: A Network Deconvolution Approach.
Proceedings of the IEEE International Conference on Acoustics, 2019

Mapping Brain Structural Connectivities to Functional Networks Via Graph Encoder-Decoder With Interpretable Latent Embeddings.
Proceedings of the 2019 IEEE Global Conference on Signal and Information Processing, 2019

Online Tensor Decomposition and Imputation for Count Data.
Proceedings of the IEEE Data Science Workshop, 2019

Online Topology Inference from Streaming Stationary Graph Signals.
Proceedings of the IEEE Data Science Workshop, 2019

Online Network Topology Inference with Partial Connectivity Informatio.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
Identifying the Topology of Undirected Networks from Diffused Non-stationary Graph Signals.
CoRR, 2018

Identifying Undirected Network Structure via Semidefinite Relaxation.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Digraph Fourier Transform via Spectral Dispersion Minimization.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs.
Proceedings of the 26th European Signal Processing Conference, 2018

Directed Network Topology Inference via Graph Filter Identification.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Spread and Sparse: Learning Interpretable Transforms for Bandlimited Signals on Directed Graphs.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Blind Identification of Graph Filters.
IEEE Trans. Signal Process., 2017

Network Topology Inference from Spectral Templates.
IEEE Trans. Signal Inf. Process. over Networks, 2017

Closing the Knowledge Gap in an Online Learning Community: Network-Analytic Discoveries, Simulation and Prediction.
CoRR, 2017

Network topology inference from non-stationary graph signals.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Robust network topology inference.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

A digraph fourier transform with spread frequency components.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

United Nations General Assembly Vote Similarity Networks.
Proceedings of the Complex Networks & Their Applications VI, 2017

2016
Analysis of Target Localization With Ideal Binary Detectors via Likelihood Function Smoothing.
IEEE Signal Process. Lett., 2016

On the Definition and Existence of a Minimum Variance Unbiased Estimator for Target Localization.
IEEE Signal Process. Lett., 2016

Network topology identification from spectral templates.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Blind identification of graph filters with multiple sparse inputs.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Rethinking sketching as sampling: Efficient approximate solution to linear inverse problems.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

SIGIBE: Solving random bilinear equations via gradient descent with spectral initialization.
Proceedings of the 24th European Signal Processing Conference, 2016

Network topology identification from imperfect spectral templates.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

Rethinking sketching as sampling: Linear transforms of graph signals.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors.
IEEE Trans. Signal Process., 2015

Decentralized learning for wireless communications and networking.
CoRR, 2015

Blind identification of graph filters with sparse inputs.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

Robust kriged Kalman filtering.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges.
Proceedings of the 2015 IEEE International Conference on Services Computing, 2015

2014
Stochastic Approximation vis-a-vis Online Learning for Big Data Analytics [Lecture Notes].
IEEE Signal Process. Mag., 2014

Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge.
IEEE Signal Process. Mag., 2014

Proximal-Gradient Algorithms for Tracking Cascades Over Social Networks.
IEEE J. Sel. Top. Signal Process., 2014

Beyond Blocks: Hyperbolic Community Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Imputation of streaming low-rank tensor data.
Proceedings of the IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, 2014

A proximal gradient algorithm for tracking cascades over networks.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Decentralized Sparsity-Regularized Rank Minimization: Algorithms and Applications.
IEEE Trans. Signal Process., 2013

Rank Regularization and Bayesian Inference for Tensor Completion and Extrapolation.
IEEE Trans. Signal Process., 2013

Load Curve Data Cleansing and Imputation Via Sparsity and Low Rank.
IEEE Trans. Smart Grid, 2013

Recovery of Low-Rank Plus Compressed Sparse Matrices With Application to Unveiling Traffic Anomalies.
IEEE Trans. Inf. Theory, 2013

Dynamic Network Cartography: Advances in Network Health Monitoring.
IEEE Signal Process. Mag., 2013

Dynamic Anomalography: Tracking Network Anomalies Via Sparsity and Low Rank.
IEEE J. Sel. Top. Signal Process., 2013

Dynamic Structural Equation Models for Social Network Topology Inference.
CoRR, 2013

Rank minimization for subspace tracking from incomplete data.
Proceedings of the IEEE International Conference on Acoustics, 2013

Inference of Poisson count processes using low-rank tensor data.
Proceedings of the IEEE International Conference on Acoustics, 2013

Dynamic structural equation models for tracking topologies of social networksy.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012
Robust PCA as Bilinear Decomposition With Outlier-Sparsity Regularization.
IEEE Trans. Signal Process., 2012

Distributed Recursive Least-Squares: Stability and Performance Analysis.
IEEE Trans. Signal Process., 2012

Robust Nonparametric Regression via Sparsity Control With Application to Load Curve Data Cleansing.
IEEE Trans. Signal Process., 2012

Dynamic Network Cartography
CoRR, 2012

In-network Sparsity-regularized Rank Minimization: Algorithms and Applications
CoRR, 2012

Exact recovery of low-rank plus compressed sparse matrices.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Nonparametric low-rank tensor imputation.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Distributed nuclear norm minimization for matrix completion.
Proceedings of the 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2012

Spatiotemporal load curve data cleansing and imputation via sparsity and low rank.
Proceedings of the IEEE Third International Conference on Smart Grid Communications, 2012

2011
Group-Lasso on Splines for Spectrum Cartography.
IEEE Trans. Signal Process., 2011

Robust nonparametric regression by controlling sparsity.
Proceedings of the IEEE International Conference on Acoustics, 2011

USPACOR: Universal sparsity-controlling outlier rejection.
Proceedings of the IEEE International Conference on Acoustics, 2011

Basis pursuit for spectrum cartography.
Proceedings of the IEEE International Conference on Acoustics, 2011

Robust conjoint analysis by controlling outlier sparsity.
Proceedings of the 19th European Signal Processing Conference, 2011

Unveiling anomalies in large-scale networks via sparsity and low rank.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011

2010
Distributed sparse linear regression.
IEEE Trans. Signal Process., 2010

Sparsity-cognizant overlapping co-clustering for behavior inference in social networks.
Proceedings of the IEEE International Conference on Acoustics, 2010

Distributed Lasso for in-network linear regression.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Distributed LMS for consensus-based in-network adaptive processing.
IEEE Trans. Signal Process., 2009

Distributed recursive least-squares for consensus-based in-network adaptive estimation.
IEEE Trans. Signal Process., 2009

Performance Analysis of the Consensus-Based Distributed LMS Algorithm.
EURASIP J. Adv. Signal Process., 2009

2008
Stability analysis of the consensus-based distributed LMS algorithm.
Proceedings of the IEEE International Conference on Acoustics, 2008


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