Panagiotis A. Traganitis

Xiao Fu

CoRR, 2024

Ensembles of Informative Representations for Self-Supervised Learning.

[BibT_eX]

[DOI]

Konstantinos D. Polyzos

Manish Kumar Singh

Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

Counting Triangles of Graphs via Matrix Partitioning.

[BibT_eX]

[DOI]

Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

A Graph Autoencoder Approach to Crowdsourcing.

[BibT_eX]

[DOI]

Charilaos I. Kanatsoulis

Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

2023

Physics-Informed Transfer Learning for Voltage Stability Margin Prediction.

[BibT_eX]

[DOI]

Manish Kumar Singh

Konstantinos D. Polyzos

Sairaj V. Dhople

Proceedings of the IEEE International Conference on Acoustics, 2023

Matrix Resolvent Eigenembeddings for Dynamic Graphs.

[BibT_eX]

[DOI]

Vasileios Kalantzis

Proceedings of the IEEE International Conference on Acoustics, 2023

Rayleigh-Ritz Based Updates of the Multilinear Singular Value Decomposition.

[BibT_eX]

[DOI]

Vasileios Kalantzis

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

Unsupervised Ensemble Classification With Sequential and Networked Data.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2022

Identifying Dependent Annotators in Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Bayesian constrained decision fusion.

[BibT_eX]

[DOI]

Proceedings of the 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2021

Bayesian Crowdsourcing with Constraints.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Detecting adversaries in Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

Identifying Spammers to Boost Crowdsourced Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Bayesian Semi-supervised Crowdsourcing.

[BibT_eX]

[DOI]

CoRR, 2020

Active Learning with Unsupervised Ensembles of Classifiers.

[BibT_eX]

[DOI]

Dimitris Berberidis

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Constrained Clustering using Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 28th European Signal Processing Conference, 2020

2019

Unsupervised Ensemble Classification with Dependent Data.

[BibT_eX]

[DOI]

CoRR, 2019

Blind Ensemble Classification of Sequential Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE Data Science Workshop, 2019

2018

Blind Multiclass Ensemble Classification.

[BibT_eX]

[DOI]

Alba Pagès-Zamora

IEEE Trans. Signal Process., 2018

Sketched Subspace Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2018

Kernel-Based Semi-Supervised Learning Over Multilayer Graphs.

[BibT_eX]

[DOI]

Vassilis N. Ioannidis

Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Blind Multi-class Ensemble Learning with Dependent Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 26th European Signal Processing Conference, 2018

2017

Blind Multi-class Ensemble Learning with Unequally Reliable Classifiers.

[BibT_eX]

[DOI]

Alba Pagès-Zamora

CoRR, 2017

Topology inference of multilayer networks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Communications Workshops, 2017

Learning from unequally reliable blind ensembles of classifiers.

[BibT_eX]

[DOI]

Alba Pagès-Zamora

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Network topology inference via elastic net structural equation models.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

Distributed sketched subspace clustering for large-scale datasets.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Nonlinear dimensionality reduction on graphs.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016

PARAFAC-based multilinear subspace clustering for tensor data.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Efficient subspace clustering of large-scale data streams with misses.

[BibT_eX]

[DOI]

Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

A randomized approach to large-scale subspace clustering.

[BibT_eX]

[DOI]

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Sketch and Validate for Big Data Clustering.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2015

Large-scale subspace clustering using sketching and validation.

[BibT_eX]

[DOI]

CoRR, 2015

Spectral clustering of large-scale communities via random sketching and validation.

[BibT_eX]

[DOI]

Proceedings of the 49th Annual Conference on Information Sciences and Systems, 2015

Large-scale subspace clustering using random sketching and validation.

[BibT_eX]

[DOI]

Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014

Clustering high-dimensional data via random sampling and consensus.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014

Big data clustering via random sketching and validation.

[BibT_eX]

[DOI]