Nicos G. Pavlidis

发表

Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification

Christoforos Anagnostopoulos, Dimitris K. Tasoulis, Niall M. Adams, 2012, Stat. Anal. Data Min..

Prospects for Bandit Solutions in Sensor Management

Niall M. Adams, Nicos G. Pavlidis, David J. Hand, 2010, Comput. J..

Evolutionary Adaptive Schemes of Probabilistic Neural Networks

Nicos G. Pavlidis, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

Adaptive consumer credit classification

Dimitris K. Tasoulis, Niall M. Adams, Nicos G. Pavlidis, 2012, J. Oper. Res. Soc..

The effect of recovery algorithms on compressive sensing background subtraction

Nicos G. Pavlidis, Lyudmila Mihaylova, Idris A. Eckley, 2013, 2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF).

Recognizing predictive patterns in chaotic maps

Nicos G. Pavlidis, Michael N. Vrahatis, Adam Adamopoulos, 2008 .

Determining the number of real roots of polynomials through neural networks

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael N. Vrahatis, 2006, Comput. Math. Appl..

Human Designed Vs. Genetically Programmed Differential Evolution Operators

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Evolving cellular automata rules for multiple-step-ahead prediction of complex binary sequences

Nicos G. Pavlidis, Michael N. Vrahatis, A. V. Adamopoulos, 2010, Math. Comput. Model..

Nonlinear dimensionality reduction for clustering

Nicos G. Pavlidis, Sotiris K. Tasoulis, Teemu Roos, 2020, Pattern Recognit..

Tracking Differential Evolution Algorithms: An Adaptive Approach through Multinomial Distribution Tracking with Exponential Forgetting

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael G. Epitropakis, 2012, SETN.

Existence and computation of short-run equilibria in economic geography

Nicos G. Pavlidis, Michael N. Vrahatis, M. N. Vrahatis, 2007, Appl. Math. Comput..

Vector evaluated differential evolution for multiobjective optimization

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael G. Epitropakis, 2011, IEEE Transactions on Evolutionary Computation.

Computational Intelligence Methods for Financial Time Series Modeling

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2006, Int. J. Bifurc. Chaos.

Parallel differential evolution

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Simulation Studies of Multi-armed Bandits with Covariates (Invited Paper)

Dimitris K. Tasoulis, Nicos G. Pavlidis, David J. Hand, 2008, Tenth International Conference on Computer Modeling and Simulation (uksim 2008).

Minimum Density Hyperplanes

Nicos G. Pavlidis, Sotiris K. Tasoulis, David P. Hofmeyr, 2015, J. Mach. Learn. Res..

Divisive clustering of high dimensional data streams

Nicos G. Pavlidis, Idris A. Eckley, David P. Hofmeyr, 2015, Statistics and Computing.

Robust Functional Regression for Outlier Detection

Nicos G. Pavlidis, David S. Leslie, Steve King, 2019, AALTD@PKDD/ECML.

Adaptive Dynamic Model Averaging with an Application to House Price Forecasting

Nicos G. Pavlidis, Alisa Yusupova, Efthymios G. Pavlidis, 2019, 1912.04661.

Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification pdf

Nicos G. Pavlidis, Idris A. Eckley, David P. Hofmeyr, 2015, ArXiv.

Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael G. Epitropakis, 2012, 2012 IEEE Congress on Evolutionary Computation.

Optimizing the Performance of Probabilistic Neural Networks in a BioinformaticsTa sk

Nicos G. Pavlidis, Michael N. Vrahatis, Vasileios L. Georgiou, 2004 .

Minimum density hyperplanes in the feature space

Nicos G. Pavlidis, Katie R. Yates, N. Pavlidis, 2016, 2016 IEEE International Conference on Big Data (Big Data).

lambda-Perceptron: An adaptive classifier for data streams

Niall M. Adams, Nicos G. Pavlidis, David J. Hand, 2011, Pattern Recognit..

Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael N. Vrahatis, 2005, Computational Intelligence.

Urinary Bladder Tumor Grade Diagnosis Using On-line Trained Neural Networks

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael N. Vrahatis, 2003, KES.

Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2006, Artif. Intell. Medicine.

PPCI: an R Package for Cluster Identification using Projection Pursuit

Nicos G. Pavlidis, David P. Hofmeyr, N. Pavlidis, 2019, R J..

Subspace Clustering of Very Sparse High-Dimensional Data

Nicos G. Pavlidis, Idris A. Eckley, Hankui Peng, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Minimum Density Hyperplane: An Unsupervised and Semi-Supervised Classifier pdf

Nicos G. Pavlidis, Sotiris K. Tasoulis, David P. Hofmeyr, 2015, ArXiv.

Dynamic Multi-Armed Bandit with Covariates

Dimitris K. Tasoulis, Niall M. Adams, Nicos G. Pavlidis, 2008, European Conference on Artificial Intelligence.

Minimum spectral connectivity projection pursuit

Nicos G. Pavlidis, Idris A. Eckley, David P. Hofmeyr, 2015, Statistics and Computing.

Maximum Clusterability Divisive Clustering

Nicos G. Pavlidis, David P. Hofmeyr, 2015, 2015 IEEE Symposium Series on Computational Intelligence.

Computational intelligence algorithms for risk-adjusted trading strategies

Nicos G. Pavlidis, Michael G. Epitropakis, Vassilis P. Plagianakos, 2007, 2007 IEEE Congress on Evolutionary Computation.

Financial forecasting through unsupervised clustering and neural networks

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2006, Oper. Res..

New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks

Nicos G. Pavlidis, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2006, Int. J. Artif. Intell. Tools.

Computational Intelligence Methods for Financial Forecasting

Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, 2013 .

Robust Function-on-Function Regression

Nicos G. Pavlidis, David S. Leslie, Steve King, 2019, Technometrics.

Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning pdf

Nicos G. Pavlidis, Hankui Peng, N. Pavlidis, 2021, ArXiv.

Computing the Number of Real Roots of Polynomials through Neural Networks

Dimitris K. Tasoulis, Nicos G. Pavlidis, Michael N. Vrahatis, 2004 .

EXCHANGE RATE FORECASTING THROUGH DISTRIBUTED TIME-LAGGED FEEDFORWARD NEURAL NETWORKS

Nicos G. Pavlidis, Michael N. Vrahatis, D. K. Tasoulis, 2004 .

Computing nash equilibria through particle swarm optimization

Nicos G. Pavlidis, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2003 .

Economic Geography: Existence, Uniqueness and Computation of Short-Run Equilibria

Nicos G. Pavlidis, Michael N. Vrahatis, P. Mossay, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).