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ORCIDNicos G. Pavlidis
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2020 – today
- 2024
[c22]Danielle Notice, Nicos G. Pavlidis, Ahmed Kheiri:
Supervised Dimensionality Reduction for the Algorithm Selection Problem. UKCI 2024: 85-97- 2023
- [c21]Danielle Notice, Ahmed Kheiri
, Nicos G. Pavlidis:
The Algorithm Selection Problem for Solving Sudoku with Metaheuristics. CEC 2023: 1-8 - [c20]Panagiotis Anagnostou, Nicos G. Pavlidis, Sotiris K. Tasoulis:
Ensemble Clustering for Boundary Detection in High-Dimensional Data. LOD (2) 2023: 324-333 - 2022
- [j19]Hankui Peng, Nicos G. Pavlidis:
Weighted sparse simplex representation: a unified framework for subspace clustering, constrained clustering, and active learning. Data Min. Knowl. Discov. 36(3): 958-986 (2022) - 2021
- [j18]Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King:
Robust Function-on-Function Regression. Technometrics 63(3): 396-409 (2021) - [i5]Hankui Peng, Nicos G. Pavlidis:
Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning. CoRR abs/2106.04330 (2021) - 2020
- [j17]Sotiris K. Tasoulis, Nicos G. Pavlidis, Teemu Roos:
Nonlinear dimensionality reduction for clustering. Pattern Recognit. 107: 107508 (2020) - [c19]Graham Laidler, Lucy E. Morgan, Barry L. Nelson, Nicos G. Pavlidis:
Metric Learning for Simulation Analytics. WSC 2020: 349-360
2010 – 2019
- 2019
- [j16]David P. Hofmeyr, Nicos G. Pavlidis:
PPCI: an R Package for Cluster Identification using Projection Pursuit. R J. 11(2): 152 (2019) - [j15]David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley:
Minimum spectral connectivity projection pursuit - Divisive clustering using optimal projections for spectral clustering. Stat. Comput. 29(2): 391-414 (2019) - [c18]Hankui Peng, Nicos G. Pavlidis:
Subspace Clustering with Active Learning. IEEE BigData 2019: 135-144 - [c17]Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King:
Robust Functional Regression for Outlier Detection. AALTD@PKDD/ECML 2019: 3-13 - [i4]Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis:
Subspace Clustering of Very Sparse High-Dimensional Data. CoRR abs/1901.09108 (2019) - [i3]Hankui Peng, Nicos G. Pavlidis:
Subspace Clustering with Active Learning. CoRR abs/1911.03299 (2019) - 2018
- [c16]Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis:
Subspace Clustering of Very Sparse High-Dimensional Data. IEEE BigData 2018: 3780-3783 - 2016
- [j14]Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis:
Minimum Density Hyperplanes. J. Mach. Learn. Res. 17: 156:1-156:33 (2016) - [j13]David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley:
Divisive clustering of high dimensional data streams. Stat. Comput. 26(5): 1101-1120 (2016) - [c15]Katie R. Yates, Nicos G. Pavlidis:
Minimum density hyperplanes in the feature space. IEEE BigData 2016: 3613-3618 - 2015
- [c14]David P. Hofmeyr, Nicos G. Pavlidis:
Maximum Clusterability Divisive Clustering. SSCI 2015: 780-786 - [i2]Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis:
Minimum Density Hyperplane: An Unsupervised and Semi-Supervised Classifier. CoRR abs/1507.04201 (2015) - [i1]David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley:
Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification. CoRR abs/1509.01546 (2015) - 2013
- [c13]Rhian Davies, Lyudmila Mihaylova, Nicos G. Pavlidis, Idris A. Eckley:
The effect of recovery algorithms on compressive sensing background subtraction. SDF 2013: 1-6 - 2012
- [j12]Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand:
Adaptive consumer credit classification. J. Oper. Res. Soc. 63(12): 1645-1654 (2012) - [j11]Christoforos Anagnostopoulos, Dimitris K. Tasoulis, Niall M. Adams, Nicos G. Pavlidis, David J. Hand:
Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification. Stat. Anal. Data Min. 5(2): 139-166 (2012) - [c12]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c11]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Tracking Differential Evolution Algorithms: An Adaptive Approach through Multinomial Distribution Tracking with Exponential Forgetting. SETN 2012: 214-222 - 2011
- [j10]Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand:
lambda-Perceptron: An adaptive classifier for data streams. Pattern Recognit. 44(1): 78-96 (2011) - [j9]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators. IEEE Trans. Evol. Comput. 15(1): 99-119 (2011) - 2010
- [j8]Nicos G. Pavlidis, Niall M. Adams, David Nicholson, David J. Hand:
Prospects for Bandit Solutions in Sensor Management. Comput. J. 53(9): 1370-1383 (2010) - [j7]Adam V. Adamopoulos, Nicos G. Pavlidis, Michael N. Vrahatis:
Evolving cellular automata rules for multiple-step-ahead prediction of complex binary sequences. Math. Comput. Model. 51(3-4): 229-238 (2010)
2000 – 2009
- 2008
- [c10]Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand:
Dynamic Multi-Armed Bandit with Covariates. ECAI 2008: 777-778 - [c9]Nicos G. Pavlidis, Dimitris K. Tasoulis, David J. Hand:
Simulation Studies of Multi-armed Bandits with Covariates. UKSim 2008: 493-498 - 2007
- [j6]Nicos G. Pavlidis, Michael N. Vrahatis, Pascal Mossay:
Existence and computation of short-run equilibria in economic geography. Appl. Math. Comput. 184(1): 93-103 (2007) - [c8]Nicos G. Pavlidis, E. G. Pavlidis, Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Computational intelligence algorithms for risk-adjusted trading strategies. IEEE Congress on Evolutionary Computation 2007: 540-547 - 2006
- [j5]Dimitris K. Tasoulis, Panagiota Spyridonos, Nicos G. Pavlidis, Vassilis P. Plagianakos, Panagiota Ravazoula, George Nikiforidis, Michael N. Vrahatis:
Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence. Artif. Intell. Medicine 38(3): 291-303 (2006) - [j4]Bernard Mourrain, Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Determining the number of real roots of polynomials through neural networks. Comput. Math. Appl. 51(3-4): 527-536 (2006) - [j3]Vasileios L. Georgiou, Nicos G. Pavlidis, Konstantinos E. Parsopoulos, Philipos D. Alevizos, Michael N. Vrahatis:
New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks. Int. J. Artif. Intell. Tools 15(3): 371-396 (2006) - [j2]Nicos G. Pavlidis, Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Computational Intelligence Methods for Financial Time Series Modeling. Int. J. Bifurc. Chaos 16(7): 2053-2062 (2006) - [j1]Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis:
Financial forecasting through unsupervised clustering and neural networks. Oper. Res. 6(2): 103-127 (2006) - [c7]Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis:
Human Designed Vs. Genetically Programmed Differential Evolution Operators. IEEE Congress on Evolutionary Computation 2006: 1880-1886 - 2005
- [c6]Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction. Computational Intelligence 2005: 456-461 - [c5]Nicos G. Pavlidis, O. K. Tasoulis, Vassilis P. Plagianakos, George Nikiforidis, Michael N. Vrahatis:
Spiking neural network training using evolutionary algorithms. IJCNN 2005: 2190-2194 - 2004
- [c4]Konstantinos E. Parsopoulos, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Vector evaluated differential evolution for multiobjective optimization. IEEE Congress on Evolutionary Computation 2004: 204-211 - [c3]Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Parallel differential evolution. IEEE Congress on Evolutionary Computation 2004: 2023-2029 - 2003
- [c2]Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Financial forecasting through unsupervised clustering and evolutionary trained neural networks. IEEE Congress on Evolutionary Computation 2003: 2314-2321 - [c1]Dimitris K. Tasoulis, Panagiota Spyridonos, Nicos G. Pavlidis, Dionisis A. Cavouras, Panagiota Ravazoula, George Nikiforidis, Michael N. Vrahatis:
Urinary Bladder Tumor Grade Diagnosis Using On-line Trained Neural Networks. KES 2003: 199-206
Coauthor Index
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