Konstantinos Koutroumbas

Orcid: 0000-0002-8480-1539

According to our database1, Konstantinos Koutroumbas authored at least 59 papers between 1994 and 2022.

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

Timeline

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Bibliography

2022
A new stochastic gradient descent possibilistic clustering algorithm.
AI Commun., 2022

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

Spectral Unmixing for Mapping a Hydrothermal Field in a Volcanic Environment Applied on ASTER, Landsat-8/OLI, and Sentinel-2 MSI Satellite Multispectral Data: The Nisyros (Greece) Case Study.
Remote. Sens., 2020

Stochastic gradient descent possibilistic clustering.
Proceedings of the SETN 2020: 11th Hellenic Conference on Artificial Intelligence, 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
Spectral Clustering.
Proceedings of the Encyclopedia of Database Systems, Second Edition, 2018

On the Convergence of the Sparse Possibilistic C-Means Algorithm.
IEEE Trans. Fuzzy Syst., 2018

Introducing Sparsity in Possibilistic Clustering: A Unified Framework and a Line Detection Paradigm.
IEEE Trans. Fuzzy Syst., 2018

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

Generalized Adaptive Possibilistic C-Means Clustering Algorithm.
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018

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

A Novel Online Generalized Possibilistic Clustering Algorithm for Big Data Processing.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Spectral Unmixing-Based Clustering of High-Spatial Resolution Hyperspectral Imagery.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 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
Variational Bayes Group Sparse Time-Adaptive Parameter Estimation With Either Known or Unknown Sparsity Pattern.
IEEE Trans. Signal Process., 2016

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

Sparsity-Aware Possibilistic Clustering Algorithms.
IEEE Trans. Fuzzy Syst., 2016

A Novel Adaptive Possibilistic Clustering Algorithm.
IEEE Trans. Fuzzy Syst., 2016

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

Detecting hyperplane clusters with adaptive possibilistic clustering.
Proceedings of the 9th Hellenic Conference on Artificial Intelligence, 2016

Hyperspectral image clustering using a novel efficient online possibilistic algorithm.
Proceedings of the 24th European Signal Processing Conference, 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

A new sparsity-aware feature selection method for hyperspectral image clustering.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Joint spectral unmixing and clustering for identifying homogeneous regions in hyperspectral images.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Online Bayesian group sparse parameter estimation using a generalized inverse Gaussian Markov chain.
Proceedings of the 23rd European Signal Processing Conference, 2015

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

2014
A Variational Bayes Framework for Sparse Adaptive Estimation.
IEEE Trans. Signal Process., 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

Sequential Sparse Adaptive Possibilistic Clustering.
Proceedings of the Artificial Intelligence: Methods and Applications, 2014

A layered sparse adaptive possibilistic approach for hyperspectral image clustering.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

Sparse adaptive possibilistic clustering.
Proceedings of the IEEE International Conference on Acoustics, 2014

Adaptive variational sparse Bayesian estimation.
Proceedings of the IEEE International Conference on Acoustics, 2014

Group-sparse adaptive variational Bayes estimation.
Proceedings of the 22nd European Signal Processing Conference, 2014

2013
A fast variational Bayes algorithm for sparse semi-supervised unmixing of OMEGA/Mars express data.
Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2013

Adaptive possibilistic clustering.
Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, 2013

Variational Bayesian sparse adaptive filtering using a Gauss-Seidel recursive approach.
Proceedings of the 21st European Signal Processing Conference, 2013

2012
A Novel Hierarchical Bayesian Approach for Sparse Semisupervised Hyperspectral Unmixing.
IEEE Trans. Signal Process., 2012

Piecewise Linear Curve Approximation Using Graph Theory and Geometrical Concepts.
IEEE Trans. Image Process., 2012

A fast algorithm for the Bayesian adaptive lasso.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Sparse semi-supervised hyperspectral unmixing using a novel iterative Bayesian inference algorithm.
Proceedings of the 19th European Signal Processing Conference, 2011

2010
On the Approximation Capabilities of Hard Limiter Feedforward Neural Networks.
Proceedings of the Artificial Intelligence: Theories, 2010

Semi-Supervised Hyperspectral Unmixing via the Weighted Lasso.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Spectral Clustering.
Proceedings of the Encyclopedia of Database Systems, 2009

2008
Pattern Recognition.
IEEE Trans. Neural Networks, 2008

A Hamming Maxnet That Determines all the Maxima.
Proceedings of the Artificial Intelligence: Theories, 2008

2007
Classification methods for random utility models with i.i.d. disturbances under the most probable alternative rule.
Eur. J. Oper. Res., 2007

2006
Discrimination of Benign from Malignant Breast Lesions Using Statistical Classifiers.
Proceedings of the Advances in Artificial Intelligence, 4th Helenic Conference on AI, 2006

2005
COMAX: A Cooperative Method for Determining the Position of the Maxima.
Neural Process. Lett., 2005

Generalized hamming networks and applications.
Neural Networks, 2005

2004
Recurrent Algorithms for Selecting the Maximum Input.
Neural Process. Lett., 2004

2003
On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes.
Neural Comput., 2003

2001
Pattern Recognition and Neural Networks.
Proceedings of the Machine Learning and Its Applications, Advanced Lectures, 2001

1999
Pattern recognition.
Academic Press, ISBN: 978-0-12-686140-2, 1999

1998
Neural network architectures for selecting the maximum input.
Int. J. Comput. Math., 1998

Divide and conquer algorithms for constructing neural networks architectures.
Proceedings of the 9th European Signal Processing Conference, 1998

1994
Qualitative analysis of the parallel and asynchronous modes of the Hamming network.
IEEE Trans. Neural Networks, 1994


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