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2020 – today
- 2024
[j25]Alexandra Anifadi, Olga Sykioti
, Konstantinos Koutroumbas, Emmanuel Vassilakis, Charalampos Vasilatos, Emil Georgiou:
Discrimination of Fe-Ni-Laterites from Bauxites Using a Novel Support Vector Machines-Based Methodology on Sentinel-2 Data. Remote. Sens. 16(13): 2295 (2024)- 2022
- [j24]Angeliki Koutsimpela, Konstantinos D. Koutroumbas:
A new stochastic gradient descent possibilistic clustering algorithm. AI Commun. 35(2): 47-64 (2022) - 2020
- [j23]Athanasia-Maria Tompolidi, Olga Sykioti, Konstantinos Koutroumbas, Issaak S. Parcharidis:
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. 12(24): 4180 (2020) - [j22]Athanasios A. Rontogiannis, Paris V. Giampouras, Konstantinos D. Koutroumbas:
Online Reweighted Least Squares Robust PCA. IEEE Signal Process. Lett. 27: 1340-1344 (2020) - [c31]Aggeliki Koutsibella, Konstantinos D. Koutroumbas:
Stochastic gradient descent possibilistic clustering. SETN 2020: 189-194
2010 – 2019
- 2019
- [j21]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Alternating Iteratively Reweighted Least Squares Minimization for Low-Rank Matrix Factorization. IEEE Trans. Signal Process. 67(2): 490-503 (2019) - [c30]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
A Projected Newton-type Algorithm for Nonnegative Matrix Factorization with Model Order Selection. ICASSP 2019: 3497-3501 - 2018
- [j20]Ioannis C. Tsaknakis, Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
A Computationally Efficient Tensor Completion Algorithm. IEEE Signal Process. Lett. 25(8): 1266-1270 (2018) - [j19]Konstantinos D. Koutroumbas, Spyridoula D. Xenaki, Athanasios A. Rontogiannis:
On the Convergence of the Sparse Possibilistic C-Means Algorithm. IEEE Trans. Fuzzy Syst. 26(1): 324-337 (2018) - [j18]Konstantinos D. Koutroumbas:
Introducing Sparsity in Possibilistic Clustering: A Unified Framework and a Line Detection Paradigm. IEEE Trans. Fuzzy Syst. 26(5): 2886-2898 (2018) - [c29]Spyridoula D. Xenaki, Konstantinos D. Koutroumbas, Athanasios A. Rontogiannis:
A Novel Online Generalized Possibilistic Clustering Algorithm for Big Data Processing. EUSIPCO 2018: 2628-2632 - [c28]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Robust PCA via Alternating Iteratively Reweighted Low-Rank Matrix Factorization. ICIP 2018: 3383-3387 - [c27]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Generalized Adaptive Possibilistic C-Means Clustering Algorithm. SETN 2018: 13:1-13:10 - [r2]Sergios Theodoridis, Konstantinos Koutroumbas:
Spectral Clustering. Encyclopedia of Database Systems (2nd ed.) 2018 - 2017
- [j17]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos E. Themelis, Konstantinos D. Koutroumbas:
Online sparse and low-rank subspace learning from incomplete data: A Bayesian view. Signal Process. 137: 199-212 (2017) - [j16]Eleftheria A. Mylona, Olga A. Sykioti, Konstantinos D. Koutroumbas, Athanasios A. Rontogiannis:
Spectral Unmixing-Based Clustering of High-Spatial Resolution Hyperspectral Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 10(8): 3711-3721 (2017) - [c26]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Low-rank and sparse NMF for joint endmembers' number estimation and blind unmixing of hyperspectral images. EUSIPCO 2017: 1430-1434 - [i6]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Low-rank and Sparse NMF for Joint Endmembers' Number Estimation and Blind Unmixing of Hyperspectral Images. CoRR abs/1703.05785 (2017) - [i5]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Alternating Iteratively Reweighted Minimization Algorithms for Low-Rank Matrix Factorization. CoRR abs/1710.02004 (2017) - 2016
- [j15]Spyridoula D. Xenaki, Konstantinos D. Koutroumbas, Athanasios A. Rontogiannis:
A Novel Adaptive Possibilistic Clustering Algorithm. IEEE Trans. Fuzzy Syst. 24(4): 791-810 (2016) - [j14]Spyridoula D. Xenaki, Konstantinos D. Koutroumbas, Athanasios A. Rontogiannis:
Sparsity-Aware Possibilistic Clustering Algorithms. IEEE Trans. Fuzzy Syst. 24(6): 1611-1626 (2016) - [j13]Paris V. Giampouras, Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing. IEEE Trans. Geosci. Remote. Sens. 54(8): 4775-4789 (2016) - [j12]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Variational Bayes Group Sparse Time-Adaptive Parameter Estimation With Either Known or Unknown Sparsity Pattern. IEEE Trans. Signal Process. 64(12): 3194-3206 (2016) - [c25]Spyridoula D. Xenaki, Konstantinos D. Koutroumbas, Athanasios A. Rontogiannis:
Hyperspectral image clustering using a novel efficient online possibilistic algorithm. EUSIPCO 2016: 2020-2024 - [c24]Konstantinos Koutroumbas, Spyridoula D. Xenaki, Athanasios A. Rontogiannis:
Detecting hyperplane clusters with adaptive possibilistic clustering. SETN 2016: 18:1-18:7 - [c23]Paris V. Giampouras, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Online low-rank subspace learning from incomplete data using rank revealing ℓ2/ℓ1 regularization. SSP 2016: 1-5 - 2015
- [c22]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Online Bayesian group sparse parameter estimation using a generalized inverse Gaussian Markov chain. EUSIPCO 2015: 1686-1690 - [c21]Paris Giampouras, Athanasios A. Rontogiannis, Konstantinos E. Themelis, Konstantinos Koutroumbas:
Online Bayesian low-rank subspace learning from partial observations. EUSIPCO 2015: 2526-2530 - [c20]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis, Olga A. Sykioti:
A new sparsity-aware feature selection method for hyperspectral image clustering. IGARSS 2015: 445-448 - [c19]Eleftheria A. Mylona, Olga A. Sykioti, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Joint spectral unmixing and clustering for identifying homogeneous regions in hyperspectral images. IGARSS 2015: 2409-2412 - [c18]Paris V. Giampouras, Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
Hyperspectral image unmixing via simultaneously sparse and low rank abundance matrix estimation. WHISPERS 2015: 1-4 - [i4]Paris Giampouras, Konstantinos Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing. CoRR abs/1504.01515 (2015) - [i3]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
On the convergence of the sparse possibilistic c-means algorithm. CoRR abs/1508.01057 (2015) - [i2]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Sparsity-aware Possibilistic Clustering Algorithms. CoRR abs/1510.04493 (2015) - 2014
- [j11]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
A Variational Bayes Framework for Sparse Adaptive Estimation. IEEE Trans. Signal Process. 62(18): 4723-4736 (2014) - [c17]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Group-sparse adaptive variational Bayes estimation. EUSIPCO 2014: 1342-1346 - [c16]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Sparse adaptive possibilistic clustering. ICASSP 2014: 3072-3076 - [c15]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Adaptive variational sparse Bayesian estimation. ICASSP 2014: 7679-7683 - [c14]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis, Olga Sykioti:
A layered sparse adaptive possibilistic approach for hyperspectral image clustering. IGARSS 2014: 2890-2893 - [c13]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Sequential Sparse Adaptive Possibilistic Clustering. SETN 2014: 29-42 - [c12]Paris V. Giampouras, Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas:
A variational Bayes algorithm for joint-sparse abundance estimation. WHISPERS 2014: 1-4 - [i1]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
A Novel Adaptive Possibilistic Clustering Algorithm. CoRR abs/1412.3613 (2014) - 2013
- [c11]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Variational Bayesian sparse adaptive filtering using a Gauss-Seidel recursive approach. EUSIPCO 2013: 1-5 - [c10]Spyridoula D. Xenaki, Konstantinos Koutroumbas, Athanasios A. Rontogiannis:
Adaptive possibilistic clustering. ISSPIT 2013: 422-427 - [c9]Athanasios A. Rontogiannis, Konstantinos Themelis, Olga Sykioti, Konstantinos Koutroumbas:
A fast variational Bayes algorithm for sparse semi-supervised unmixing of OMEGA/Mars express data. WHISPERS 2013: 1-4 - 2012
- [j10]Konstantinos Koutroumbas:
Piecewise Linear Curve Approximation Using Graph Theory and Geometrical Concepts. IEEE Trans. Image Process. 21(9): 3877-3887 (2012) - [j9]Konstantinos Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
A Novel Hierarchical Bayesian Approach for Sparse Semisupervised Hyperspectral Unmixing. IEEE Trans. Signal Process. 60(2): 585-599 (2012) - [c8]Athanasios A. Rontogiannis, Konstantinos E. Themelis, Konstantinos Koutroumbas:
A fast algorithm for the Bayesian adaptive lasso. EUSIPCO 2012: 974-978 - 2011
- [c7]Konstantinos E. Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Sparse semi-supervised hyperspectral unmixing using a novel iterative Bayesian inference algorithm. EUSIPCO 2011: 1165-1169 - 2010
- [c6]Konstantinos Themelis, Athanasios A. Rontogiannis, Konstantinos Koutroumbas:
Semi-Supervised Hyperspectral Unmixing via the Weighted Lasso. ICASSP 2010: 1194-1197 - [c5]Konstantinos Koutroumbas, Yannis Bakopoulos:
On the Approximation Capabilities of Hard Limiter Feedforward Neural Networks. SETN 2010: 163-172
2000 – 2009
- 2009
- [r1]Sergios Theodoridis, Konstantinos Koutroumbas:
Spectral Clustering. Encyclopedia of Database Systems 2009: 2748-2752 - 2008
- [j8]Sergios Theodoridis, Konstantinos Koutroumbas:
Pattern Recognition. IEEE Trans. Neural Networks 19(2): 376 (2008) - [c4]Konstantinos Koutroumbas:
A Hamming Maxnet That Determines all the Maxima. SETN 2008: 135-147 - 2007
- [j7]Nicholas Kalouptsidis, Konstantinos Koutroumbas, V. Psaraki:
Classification methods for random utility models with i.i.d. disturbances under the most probable alternative rule. Eur. J. Oper. Res. 176(3): 1778-1794 (2007) - 2006
- [c3]Konstantinos Koutroumbas, Abraham Pouliakis, Tatiana Mona Megalopoulou, John Georgoulakis, Anna-Eva Giachnaki, Petros Karakitsos:
Discrimination of Benign from Malignant Breast Lesions Using Statistical Classifiers. SETN 2006: 543-546 - 2005
- [j6]Konstantinos Koutroumbas, Nicholas Kalouptsidis:
Generalized hamming networks and applications. Neural Networks 18(7): 896-913 (2005) - [j5]Konstantinos Koutroumbas:
COMAX: A Cooperative Method for Determining the Position of the Maxima. Neural Process. Lett. 22(2): 205-221 (2005) - 2004
- [j4]Konstantinos Koutroumbas:
Recurrent Algorithms for Selecting the Maximum Input. Neural Process. Lett. 20(3): 179-197 (2004) - 2003
- [j3]Konstantinos Koutroumbas:
On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes. Neural Comput. 15(10): 2457-2481 (2003) - 2001
- [c2]Sergios Theodoridis, Konstantinos Koutroumbas:
Pattern Recognition and Neural Networks. Machine Learning and Its Applications 2001: 169-195
1990 – 1999
- 1999
- [b1]Sergios Theodoridis, Konstantinos Koutroumbas:
Pattern recognition. Academic Press 1999, ISBN 978-0-12-686140-2, pp. I-XIV, 1-625 - 1998
- [j2]Konstantinos Koutroumbas, Nicholas Kalouptsidis:
Neural network architectures for selecting the maximum input. Int. J. Comput. Math. 67(1-2): 25-32 (1998) - [c1]Konstantinos Koutroumbas, Abraham Pouliakis, Nicholas Kalouptsidis:
Divide and conquer algorithms for constructing neural networks architectures. EUSIPCO 1998: 1-4 - 1994
- [j1]Konstantinos Koutroumbas, Nicholas Kalouptsidis:
Qualitative analysis of the parallel and asynchronous modes of the Hamming network. IEEE Trans. Neural Networks 5(3): 380-391 (1994)
Coauthor Index
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