Nicos G. Pavlidis

Publication Activity (10 Years)

Years Active: 2003-2023
Publications (10 Years): 17

Top Topics

Unsupervised Classification

Boundary Detection

Subspace Clustering

Dimensional Data

Top Venues

Pattern Recognit.

Publications

Panagiotis Anagnostou, Nicos G. Pavlidis, Sotiris K. Tasoulis
Ensemble Clustering for Boundary Detection in High-Dimensional Data. LOD (2) (2023)
Danielle Notice, Ahmed Kheiri, Nicos G. Pavlidis
The Algorithm Selection Problem for Solving Sudoku with Metaheuristics. CEC (2023)
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) (2022)
Hankui Peng, Nicos G. Pavlidis
Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning. CoRR (2021)
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
Robust Function-on-Function Regression. Technometrics 63 (3) (2021)
Sotiris K. Tasoulis, Nicos G. Pavlidis, Teemu Roos
Nonlinear dimensionality reduction for clustering. Pattern Recognit. 107 (2020)
Graham Laidler, Lucy E. Morgan, Barry L. Nelson, Nicos G. Pavlidis
Metric Learning for Simulation Analytics. WSC (2020)
Hankui Peng, Nicos G. Pavlidis
Subspace Clustering with Active Learning. CoRR (2019)
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) (2019)
Hankui Peng, Nicos G. Pavlidis
Subspace Clustering with Active Learning. IEEE BigData (2019)
Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
Robust Functional Regression for Outlier Detection. AALTD@PKDD/ECML (2019)
Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis
Subspace Clustering of Very Sparse High-Dimensional Data. CoRR (2019)
David P. Hofmeyr, Nicos G. Pavlidis
PPCI: an R Package for Cluster Identification using Projection Pursuit. R J. 11 (2) (2019)
Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis
Subspace Clustering of Very Sparse High-Dimensional Data. IEEE BigData (2018)
David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley
Divisive clustering of high dimensional data streams. Stat. Comput. 26 (5) (2016)
Katie R. Yates, Nicos G. Pavlidis
Minimum density hyperplanes in the feature space. IEEE BigData (2016)
Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis
Minimum Density Hyperplanes. J. Mach. Learn. Res. 17 (2016)
Nicos G. Pavlidis, David P. Hofmeyr, Sotiris K. Tasoulis
Minimum Density Hyperplane: An Unsupervised and Semi-Supervised Classifier. CoRR (2015)
David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley
Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification. CoRR (2015)
David P. Hofmeyr, Nicos G. Pavlidis
Maximum Clusterability Divisive Clustering. SSCI (2015)
Rhian Davies, Lyudmila Mihaylova, Nicos G. Pavlidis, Idris A. Eckley
The effect of recovery algorithms on compressive sensing background subtraction. SDF (2013)
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) (2012)
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)
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)
Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand
Adaptive consumer credit classification. J. Oper. Res. Soc. 63 (12) (2012)
Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand
lambda-Perceptron: An adaptive classifier for data streams. Pattern Recognit. 44 (1) (2011)
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) (2011)
Nicos G. Pavlidis, Niall M. Adams, David Nicholson, David J. Hand
Prospects for Bandit Solutions in Sensor Management. Comput. J. 53 (9) (2010)
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) (2010)
Nicos G. Pavlidis, Dimitris K. Tasoulis, Niall M. Adams, David J. Hand
Dynamic Multi-Armed Bandit with Covariates. ECAI (2008)
Nicos G. Pavlidis, Dimitris K. Tasoulis, David J. Hand
Simulation Studies of Multi-armed Bandits with Covariates. UKSim (2008)
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)
Nicos G. Pavlidis, Michael N. Vrahatis, P. Mossay
Existence and computation of short-run equilibria in economic geography. Appl. Math. Comput. 184 (1) (2007)
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) (2006)
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) (2006)
Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis
Financial forecasting through unsupervised clustering and neural networks. Oper. Res. 6 (2) (2006)
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) (2006)
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)
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) (2006)
Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis
Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction. Computational Intelligence (2005)
Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis
Parallel differential evolution. IEEE Congress on Evolutionary Computation (2004)
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)
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)
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)