Paris Giampouras

Orcid: 0000-0003-2039-0758

According to our database1, Paris Giampouras authored at least 26 papers between 2013 and 2023.

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

Timeline

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Links

On csauthors.net:

Bibliography

2023
Online rank-revealing block-term tensor decomposition.
Signal Process., November, 2023

A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions.
CoRR, 2023

The Ideal Continual Learner: An Agent That Never Forgets.
Proceedings of the International Conference on Machine Learning, 2023

Clustering-based Domain-Incremental Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Block-Term Tensor Decomposition Model Selection and Computation: The Bayesian Way.
IEEE Trans. Signal Process., 2022

Reverse Engineering ℓ<sub>p</sub> attacks: A block-sparse optimization approach with recovery guarantees.
Proceedings of the International Conference on Machine Learning, 2022

Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension.
Proceedings of the Tenth International Conference on Learning Representations, 2022

A Projected Newton-type Algorithm for Rank - revealing Nonnegative Block - Term Tensor Decomposition.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Block-Term Tensor Decomposition: Model Selection and Computation.
IEEE J. Sel. Top. Signal Process., 2021

Rank-Revealing Block-Term Decomposition for Tensor Completion.
Proceedings of the IEEE International Conference on Acoustics, 2021

A Bayesian Approach to Block-Term Tensor Decomposition Model Selection and Computation.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Online Reweighted Least Squares Robust PCA.
IEEE Signal Process. Lett., 2020

A novel variational form of the Schatten-$p$ quasi-norm.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Alternating Iteratively Reweighted Least Squares Minimization for Low-Rank Matrix Factorization.
IEEE Trans. Signal Process., 2019

A Projected Newton-type Algorithm for Nonnegative Matrix Factorization with Model Order Selection.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
A Computationally Efficient Tensor Completion Algorithm.
IEEE Signal Process. Lett., 2018

Robust PCA via Alternating Iteratively Reweighted Low-Rank Matrix Factorization.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2017
Online sparse and low-rank subspace learning from incomplete data: A Bayesian view.
Signal Process., 2017

Alternating Iteratively Reweighted Minimization Algorithms for Low-Rank Matrix Factorization.
CoRR, 2017

Low-rank and sparse NMF for joint endmembers' number estimation and blind unmixing of hyperspectral images.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing.
IEEE Trans. Geosci. Remote. Sens., 2016

Online low-rank subspace learning from incomplete data using rank revealing ℓ2/ℓ1 regularization.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

2015
Hyperspectral image unmixing via simultaneously sparse and low rank abundance matrix estimation.
Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2015

Online Bayesian low-rank subspace learning from partial observations.
Proceedings of the 23rd European Signal Processing Conference, 2015

2014
A variational Bayes algorithm for joint-sparse abundance estimation.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014

2013
Artificial Neural Network Approach for Land Cover Classification of Fused Hyperspectral and Lidar Data.
Proceedings of the Artificial Intelligence Applications and Innovations, 2013


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