M. N. Vrahatis

发表

Estimating the number of clusters using a windowing technique

B. Boutsinas, D. K. Tasoulis, M. N. Vrahatis, 2006, Pattern Recognition and Image Analysis.

Density Based Text Clustering

D. K. Tasoulis, M. N. Vrahatis, E. K. Ikonomakis, 2019, Recent Progress in Computational Sciences and Engineering.

Detecting Resonances using Evolutionary Algorithms

M. N. Vrahatis, Y. G. Petalas, C. G. Antonopoulos, 2019, Recent Progress in Computational Sciences and Engineering.

Advances in computational intelligence: theory, methods, appli- cations

M. N. Vrahatis, G. D. Magoulas, 2005 .

Novel Approaches to Unsupervised Clustering Through k-Windows Algorithm

M. N. Vrahatis, D. K. Tasoulis, D. Tasoulis, 2005 .

Computing Nash equilibria through computational intelligence methods

M. N. Vrahatis, N. Pavlidis, K. Parsopoulos, 2005 .

A New Unconstrained Optimization Method for Imprecise Function and Gradient Values

M. N. Vrahatis, G. Androulakis, G. Manoussakis, 1996 .

Particle swarm optimization for integer programming

Michael N. Vrahatis, E. C. Laskari, Konstantinos E. Parsopoulos, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Objective function “stretching” to alleviate convergence to local minima

M. N. Vrahatis, K. Parsopoulos, V. Plagianakos, 2001 .

Adaptive stepsize algorithms for on-line training of neural networks

M. N. Vrahatis, V. Plagianakos, G. Magoulas, 2001 .

Ordinary Differential Equations In Theory and Practice

M. N. Vrahatis, M. Vrahatis, 1997, IEEE Computational Science and Engineering.

Memetic particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Yiannis G. Petalas, 2007, Ann. Oper. Res..

MEMETIC ALGORITHMS FOR NEURAL NETWORK TRAINING ON MEDICAL DATA

M. N. Vrahatis, Y. G. Petalas, .

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks using the Nash Bargaining Solution

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2005, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Multi-Objective Particles Swarm Optimization Approaches

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2008 .

Generalizations of the Intermediate Value Theorem for Approximating Fixed Points and Zeros of Continuous Functions

Michael N. Vrahatis, M. N. Vrahatis, 2019, NUMTA.

Generalization of the Bolzano theorem for simplices

M. N. Vrahatis, M. Vrahatis, 2016 .

Erratum to: "RFSFNS: A portable package for the numerical determination of the number and the calculation of roots of Bessel functions" [Comput. Phys. Commun. 92 (1995) 252-266]

M. N. Vrahatis, O. Ragos, T. Skiniotis, 1999 .

Intermediate value theorem for simplices for simplicial approximation of fixed points and zeros

M. N. Vrahatis, 2020 .

A dimension-reducing method for unconstrained optimization

Michael N. Vrahatis, T. N. Grapsa, M. N. Vrahatis, 1996 .

Aitken and Neville Inverse Interpolation Methods over Finite Fields

Michael N. Vrahatis, E. C. Laskari, G. C. Meletiou, 2005 .

A new dimension-reducing method for solving systems of nonlinear equations

Michael N. Vrahatis, T. N. Grapsa, M. N. Vrahatis, 1990 .

Homoclinic orbits of invertible maps

M. N. Vrahatis, T. Bountis, J. Bergamin, 2002 .

OPTAC: a portable software package for analyzing and comparing optimization methods by visualization

M. N. Vrahatis, G. Androulakis, 1996 .

Chapter 2 LEARNING RATE ADAPTATION IN STOCHASTIC GRADIENT DESCENT

M. N. Vrahatis, G. D. Magoulas, V. Plagianakos, 2001 .

On the acceleration of the backpropagation training method

M. N. Vrahatis, G. Androulakis, G. Magoulas, 1997 .

From linear to nonlinear iterative methods

M. N. Vrahatis, V. Plagianakos, G. Magoulas, 2003 .

Data Mining using Nonmonotonic Connectionist Expert Systems

M. N. Vrahatis, M. Vrahatis, 1999 .

SMALLER ALIGNMENT INDEX (SALI): DETERMINING THE ORDERED OR CHAOTIC NATURE OF ORBITS IN CONSERVATIVE DYNAMICAL SYSTEMS

M. N. Vrahatis, C. Antonopoulos, Ch. Skokos, 2002, nlin/0210053.

Detecting order and chaos in Hamiltonian systems by the SALI method

M. N. Vrahatis, C. Antonopoulos, Ch. Skokos, 2004, nlin/0404058.

Genetic Algorithm Evolution of Cellular Automata Rules for Complex Binary Sequence Prediction

M. N. Vrahatis, N. Pavlidis, A. Adamopoulos, 2005 .

Designing S-boxes through Evolutionary Computation

M. N. Vrahatis, Brill Academic Publishers, 2006 .

Problems of cryptography as discrete optimization tasks

M. N. Vrahatis, E. Laskari, G. Meletiou, 2005 .

Evolutionary computation based cryptanalysis: A first study

M. N. Vrahatis, Y. Stamatiou, E. Laskari, 2005 .

The Discrete Logarithm Problem as an Optimization Task : A First Study

M. N. Vrahatis, E. Laskari, G. Meletiou, 2003 .

COMPUTING PERIODIC ORBITS OF NONLINEAR MAPPINGS THROUGH PARTICLE SWARM OPTIMIZATION

M. N. Vrahatis, K. Parsopoulos, 2002 .

Particle Identification by Light Scattering through Evolutionary Algorithms

M. N. Vrahatis, K. Parsopoulos, E. Laskari, 2002 .

A class of gradient unconstrained minimization algorithms with adaptive stepsize - some corrections

M. N. Vrahatis, G. Androulakis, G. Magoulas, 2000 .

Optimizing Trading Strategies through Genetic Programming

M. N. Vrahatis, N. Pavlidis, E. Pavlidis, 2006 .

Detecting resonances in conservative maps using evolutionary algorithms

Michael N. Vrahatis, Chris G. Antonopoulos, Tassos Bountis, 2009 .

Studying the performance of artificial neural networks on problems related to cryptography

Dimitris K. Tasoulis, Michael N. Vrahatis, E. C. Laskari, 2006 .

Fuzzy Cognitive Maps Learning using Memetic Algorithms

E. I. Papageorgiou, P. P. Groumpos, M. N. Vrahatis, 2005 .

Evolutionary Generation of Runge-Kutta Pairs

M. N. Vrahatis, Y. G. Petalas, G. Androulakis, 2006 .

Globally Convergent Modi ¢ cation of the Quickprop Method

M. N. Vrahatis, G. D. Magoulas, V. Plagianakos, 2000 .

How Does the Smaller Alignment Index (SALI) Distinguish Order from Chaos

Michael N. Vrahatis, Chris G. Antonopoulos, Tassos Bountis, 2003, nlin/0301035.

Utilizing Evolutionary Computation Methods for the Design of S-Boxes

M. N. Vrahatis, E. Laskari, G. Meletiou, 2006, 2006 International Conference on Computational Intelligence and Security.

Unified Particle Swarm Optimization for Hadamard matrices of Williamson type

C. Koukouvinos, M. N. Vrahatis, K. Parsopoulos, 2006 .

Analysis With Grey Data : The Grey Eigenvalue Problem

M. N. Vrahatis, P. Alevizos, Y. Theodorou, 2016 .

Optimal Rational Approximation Number Sets: Application to Nonlinear Dynamics in Particle Accelerators

M. N. Vrahatis, N. Daras, M. Vrahatis, 2016 .

Threshold Secret Sharing Through Multivariate Birkhoff Interpolation

M. N. Vrahatis, G. Meletiou, Vasileios E. Markoutis, 2015 .

RECENT ADVANCES IN FUZZY COGNITIVE MAPS LEARNING USING EVOLUTIONARY COMPUTATION TECHNIQUES

E. I. Papageorgiou, P. P. Groumpos, M. N. Vrahatis, 2004 .

Integer Weight Higher-Order Neural Network Training Using Distributed Differential Evolution

M. N. Vrahatis, V. Plagianakos, M. G. Epitropakis, 2019, Recent Progress in Computational Sciences and Engineering.

Efficient Evolutionary Unsupervised Clustering

D. K. Tasoulis, M. N. Vrahatis, V. Plagianakos, 2005 .

Handling problems in cryptography with matrix factorization

M. N. Vrahatis, G. Meletiou, D. Triantafyllou, 2015 .

Novel Approaches in Unsupervised Clustering

D. K. Tasoulis, M. N. Vrahatis, D. Tasoulis, 2004 .

TUMOR DETECTION IN COLONOSCOPY USING THE UNSUPERVISED k-WINDOWS CLUSTERING ALGORITHM AND NEURAL NETWORKS

V. P. Plagianakos, D. K. Tasoulis, M. N. Vrahatis, 2004 .

EFFICIENT UNSUPERVISED CLUSTERING THROUGH INTELLIGENT OPTIMIZATION

M. N. Vrahatis, E. K. Ikonomakis, G. S. Antzoulatos, 2009 .

Particle swarm optimization : an efficient method for tracing periodic orbits in three-dimensional galactic potentials

P. A. Patsis, M. N. Vrahatis, Ch. Skokos, 2005 .

Stochastic Optimization for Detecting Periodic Orbits of Nonlinear Mappings

M. N. Vrahatis, Y. G. Petalas, K. E. Parsopoulos, 2008 .

DIMENSION REDUCING METHODS FOR SYSTEMS OF NONLINEAR EQUATIONS AND UNCONSTRAINED OPTIMIZATION : A REVIEW

T. N. Grapsa, M. N. Vrahatis, T. Grapsa, 2003 .

Global Optimization for Imprecise Problems

D. G. Sotiropoulos, M. N. Vrahatis, E. Triantafyllou, 1997 .

Chapter 1 SUPERVISED TRAINING USING GLOBAL SEARCH METHODS

M. N. Vrahatis, G. D. Magoulas, V. Plagianakos, 2001 .

Global Search Methods for Neural Network Training

M. N. Vrahatis, G. D. Magoulas, G. Androulakis, 1999 .

FORECASTING USING COMPUTATIONAL INTELLIGENCE METHODS

M. N. Vrahatis, N. Pavlidis, 2004 .

Locally recurrent neural networks

M. N. Vrahatis, K. Parsopoulos, N. Fakotakis, 2018 .

Generating Symmetric Composition Methods through Memetic Algorithms

M. N. Vrahatis, Brill Academic Publishers, 2006 .

RFSFNS: A portable package for the numerical determination of the number and the calculation of roots of Bessel functions

Michael N. Vrahatis, O. Ragos, T. N. Grapsa, 1995 .

Isolation of Real Roots and Computation of the Topological Degree

M. N. Vrahatis, B. Mourrain, Jean-Claude Yakoubsohn, 2001 .

A TRAINING METHOD FOR DISCRETE

M. N. Vrahatis, G. Androulakis, G. Magoulas, 1997 .

Expected Behavior of Bisection Based Methods for Counting and Computing the Roots of a Function

M. N. Vrahatis, F. S. Makri, D. Kavvadias, 1999 .

POPULATION SIZE TRADEOFFS IN DE AND PSO-BASED METHODS FOR PNN TRAINING

M. N. Vrahatis, T. Ganchev, Nikolay T. Dukov, 2015 .

Nonlinear Data Fitting for Landslides Modeling

Michael N. Vrahatis, Stathis C. Stiros, Konstantinos E. Parsopoulos, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

Interval Cognitive Maps

M. N. Vrahatis, Y. G. Petalas, K. Parsopoulos, 2005 .

Preface Special issue

M. N. Vrahatis, A. Hadjidimos, I. Kotsireas, 2016 .

An alliance between Cyprus and Greece: assessing its partners’ relative security contribution

Michael N. Vrahatis, Konstantinos E. Parsopoulos, George A. Zombanakis, 2004 .

Optimal versus required defence expenditure: The case of the Greek-Turkish arms race

M. N. Vrahatis, K. Parsopoulos, G. Zombanakis, 2002 .

E-EVALUATION IN OPEN AND DISTANCE LEARNING ENVIRONMENTS

M. N. Vrahatis, E. Laskari, G. Meletiou, 2009 .

Parameter Optimization Algorithm with Improved Convergence Properties for Adaptive Learning

M. N. Vrahatis, G. Magoulas, M. Vrahatis, 2022 .

Evolvingcellularautomatarulesformultiple-step-aheadpredictionof complexbinarysequences

M. N. Vrahatis, N. Pavlidis, U. Patras, 2010 .

Application of the Characteristic Bisection Method for locating and computing periodic orbits in molecular systems

Michael N. Vrahatis, Stavros C. Farantos, K. E. Papadakis, 2001 .

COMPUTATION AND STABILITY OF PERIODIC ORBITS OF NONLINEAR MAPPINGS

M. N. Vrahatis, Ch. Skokos, T. Bountis, 2002 .

Application of efficient composite methods for computing with certainty periodic orbits in molecular systems

M. N. Vrahatis, V. Kalantonis, E. Perdios, 2002 .

2D universality of period-doubling bifurcations in 3D conservative reversible mappings

M. N. Vrahatis, T. Bountis, S. Komineas, 1994 .

Survey of Methods for Solving Systems of Nonlinear Equations, Part II: Optimization Based Approaches

M. N. Vrahatis, P. Pardalos, I. Kotsireas, 2022, ArXiv.

Survey of Methods for Solving Systems of Nonlinear Equations, Part I: Root-finding Approaches

M. N. Vrahatis, P. Pardalos, I. Kotsireas, 2022, ArXiv.

Introduction to Artificial Neural Networks Training and Applications

M. N. Vrahatis, G. D. Magoulas, K. Parsopoulos, 2010 .

Interval analysis to address uncertainty in multicriteria energy market clearance

M. N. Vrahatis, G. Papavassilopoulos, Panagiotis Kontogiorgos, 2014 .

Preface [Special issue: NumAn 2012]

M. N. Vrahatis, A. Hadjidimos, I. Kotsireas, 2016 .

Lateral molecular interaction on heterogeneous surfaces experimentally measured

N. A. Katsanos, M. N. Vrahatis, V. Plagianakos, 2002 .

ZEBEC: A mathematical software package for computing simple zeros of Bessel functions of real order and complex argument

Michael N. Vrahatis, Peter Kravanja, O. Ragos, 1998 .

Survey on Generalizations of the Intermediate Value Theorem and Applications

M. N. Vrahatis, 2022, CASC.

Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach

George D. Magoulas, Dimitris A. Karras, Michael N. Vrahatis, 2016, J. Mach. Learn. Res..

Content driven clustering algorithm combining density and distance functions

Michael N. Vrahatis, George M. Spyrou, M. N. Vrahatis, 2019, Pattern Recognit..

A Clustering Strategy for the Key Segmentation of Musical Audio

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2013, Computer Music Journal.

Computational Intelligence Algorithms and DNA Microarrays

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2008, Computational Intelligence in Bioinformatics.

Generalizing the k-Windows clustering algorithm in metric spaces

Dimitris K. Tasoulis, Michael N. Vrahatis, M. N. Vrahatis, 2007, Math. Comput. Model..

Generalized locally recurrent probabilistic neural networks with application to text-independent speaker verification

Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis, 2007, Neurocomputing.

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.

Unsupervised clustering in mRNA expression profiles

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2006, Comput. Biol. Medicine.

Computational Intelligence Methods for Financial Time Series Modeling

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

Financial forecasting through unsupervised clustering and neural networks

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

Computational intelligence techniques for acute leukemia gene expression data classification

V.P. Plagianakos, M.N. Vrahatis, M. N. Vrahatis, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Clustering in evolutionary algorithms to efficiently compute simultaneously local and global minima

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2005, 2005 IEEE Congress on Evolutionary Computation.

Unsupervised clustering on dynamic databases

Dimitris K. Tasoulis, Michael N. Vrahatis, M. N. Vrahatis, 2005, Pattern Recognit. Lett..

Unsupervised distributed clustering

Dimitris K. Tasoulis, Michael N. Vrahatis, M. N. Vrahatis, 2004, Parallel and Distributed Computing and Networks.

Unsupervised Clustering of Bioinformatics Data

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2004 .

Computing with certainty individual members of families of periodic orbits of a given period

Michael N. Vrahatis, M. N. Vrahatis, A. E. Perdiou, 2001 .

Locating and Computing Arbitrarily Distributed Zeros

Michael N. Vrahatis, Dimitris J. Kavvadias, Frosso S. Makri, 1999, SIAM J. Sci. Comput..

Evolutionary Computation Techniques for Optimizing Fuzzy Cognitive Maps in Radiation Therapy Systems

Michael N. Vrahatis, Elpiniki I. Papageorgiou, Peter P. Groumpos, 2004, GECCO.

p-MEMPSODE: Parallel and irregular memetic global optimization

Michael N. Vrahatis, Dimitris G. Papageorgiou, Isaac E. Lagaris, 2015, Comput. Phys. Commun..

MEMPSODE: A global optimization software based on hybridization of population-based algorithms and local searches

Michael N. Vrahatis, Dimitris G. Papageorgiou, Isaac E. Lagaris, 2012, Comput. Phys. Commun..

Improving fuzzy cognitive maps learning through memetic particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Yiannis G. Petalas, 2008, Soft Comput..

Entropy-based Memetic Particle Swarm Optimization for computing periodic orbits of nonlinear mappings

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Yiannis G. Petalas, 2007, 2007 IEEE Congress on Evolutionary Computation.

Partially Connected Locally Recurrent Probabilistic Neural Networks

M. N. Vrahatis, K. Parsopoulos, N. Fakotakis, 2008 .

Fuzzy Evolutionary Probabilistic Neural Networks

Michael N. Vrahatis, Vasileios L. Georgiou, Philipos D. Alevizos, 2008, ANNPR.

Locating and computing in parallel all the simple roots of special functions using PVM

Vassilis P. Plagianakos, Michael N. Vrahatis, N. K. Nousis, 2001 .

Artificial nonmonotonic neural networks

Michael N. Vrahatis, Basilis Boutsinas, M. N. Vrahatis, 2001, Artif. Intell..

Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2005, ICNC.

Cryptography , Network Security and Applications in the Armed Forces

Michael N. Vrahatis, G. C. Meletiou, M. N. Vrahatis, 2014 .

Interactive Evolution of 8-Bit Melodies with Genetic Programming towards Finding Aesthetic Measures for Sound

Michael G. Epitropakis, Michael N. Vrahatis, Andreas Floros, 2012, EvoMUSART.

Evaluation of PNN pattern-layer activation function approximations in different training setups

Michael N. Vrahatis, Todor Ganchev, Nikolay Dukov, 2019, International Journal of Speech Technology.

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).

Incorporating Fuzzy Membership Functions into Evolutionary Probabilistic Neural Networks

Michael N. Vrahatis, Vasileios L. Georgiou, D. Alevizos, 2019, Recent Progress in Computational Sciences and Engineering.

Musical Composer Identification through Probabilistic and Feedforward Neural Networks

Michael G. Epitropakis, Michael N. Vrahatis, Maximos A. Kaliakatsos-Papakostas, 2010, EvoApplications.

Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Sonia Malefaki, 2009, LION.

Novel Approaches to Probabilistic Neural Networks Through Bagging and Evolutionary Estimating of Prior Probabilities

Michael N. Vrahatis, Vasileios L. Georgiou, Philipos D. Alevizos, 2008, Neural Processing Letters.

Cryptography and Cryptanalysis Through Computational Intelligence

Michael N. Vrahatis, Yannis C. Stamatiou, Elena C. Laskari, 2007, Computational Intelligence in Information Assurance and Security.

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.

Evolutionary Bayesian Probabilistic Neural Networks

Michael N. Vrahatis, Sonia Malefaki, Vasileios L. Georgiou, 2006 .

Generalized locally recurrent probabilistic neural networks for text-independent speaker verification

Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Locally Recurrent Probabilistic Neural Networks with Application to Speaker Verification

Todor Ganchev, Dimitris K. Tasoulis, Michael N. Vrahatis, 2004 .

Optimizing the Performance of Probabilistic Neural Networks in a BioinformaticsTa sk

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

Cryptography through Interpolation, Approximation and Computational Intelligence Methods

Dimitris K. Tasoulis, Michael N. Vrahatis, G. C. Meletiou, 2003 .

An integrated genetic and cytogenetic map for the Mediterranean fruit fly, Ceratitis capitata, based on microsatellite and morphological markers

M. N. Vrahatis, Y. G. Petalas, A. Zacharopoulou, 2008, Genetica.

Feature Selection in Single-Cell RNA-seq Data via a Genetic Algorithm

Michael N. Vrahatis, Sotiris K. Tasoulis, Aristidis G. Vrahatis, 2021, LION.

New globally convergent training scheme based on the resilient propagation algorithm

George D. Magoulas, Michael N. Vrahatis, Aristoklis D. Anastasiadis, 2005, Neurocomputing.

Enhanced Learning in Fuzzy Simulation Models Using Memetic Particle Swarm Optimization

Michael N. Vrahatis, Elpiniki I. Papageorgiou, Peter P. Groumpos, 2007, 2007 IEEE Swarm Intelligence Symposium.

Recent approaches to global optimization problems through Particle Swarm Optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2002, Natural Computing.

A chemical energy approach of avascular tumor growth: multiscale modeling and qualitative results

M. N. Vrahatis, G. Dassios, H. Kourea, 2015, SpringerPlus.

No Free Lunch Theorem: A Review

Panos M. Pardalos, Michael N. Vrahatis, Stavros P. Adam, 2019, Approximation and Optimization.

Adaptive Algorithms for Neural Network Supervised Learning: a Deterministic Optimization Approach

George D. Magoulas, Michael N. Vrahatis, M. N. Vrahatis, 2006, Int. J. Bifurc. Chaos.

Chaos and Music: from Time Series Analysis to Evolutionary Composition

Michael G. Epitropakis, Michael N. Vrahatis, Andreas Floros, 2013, Int. J. Bifurc. Chaos.

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

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

Tuning PSO Parameters Through Sensitivity Analysis

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Thomas Beielstein, 2002 .

Analysis of Particle Swarm Optimization Using Computational Statistics

Thomas Bartz-Beielstein, Michael N. Vrahatis, M. N. Vrahatis, 2004 .

A Review of Major Application Areas of Differential Evolution

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2008 .

The new window density function for efficient evolutionary unsupervised clustering

Dimitris K. Tasoulis, Michael N. Vrahatis, M. N. Vrahatis, 2005, 2005 IEEE Congress on Evolutionary Computation.

Differential Evolution Algorithms for Finding Predictive Gene Subsets in Microarray Data

Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2006, AIAI.

Design and Analysis of Optimization Algorithms Using Computational Statistics

Thomas Bartz-Beielstein, Michael N. Vrahatis, M. N. Vrahatis, 2004 .

Determining the number of real roots of polynomials through neural networks

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

Spiking neural network training using evolutionary algorithms

V.P. Plagianakos, M.N. Vrahatis, M. N. Vrahatis, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction

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

Computing the Number of Real Roots of Polynomials through Neural Networks

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

Financial forecasting through unsupervised clustering and evolutionary trained neural networks

Dimitris K. Tasoulis, Michael N. Vrahatis, M. N. Vrahatis, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

A FIRST STUDY OF THE NEURAL NETWORK APPROACH IN THE RSA CRYPTOSYSTEM

Michael N. Vrahatis, G. C. Meletiou, M. N. Vrahatis, 2002 .

10 Intelligent Music Composition

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2013 .

Multi-Objective Evolutionary Optimization Algorithms for Machine Learning: A Recent Survey

Michael N. Vrahatis, Sotiris Kotsiantis, Christos K. Aridas, 2019, Approximation and Optimization.

Structure and Breakdown of Invariant Tori in a 4-D Mapping Model of Accelerator Dynamics

Michael N. Vrahatis, Heinz Isliker, M. N. Vrahatis, 1997 .

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).

ZEAL: A mathematical software package for computing zeros of analytic functions

Michael N. Vrahatis, Peter Kravanja, O. Ragos, 2000 .

Multi-Objective Particles Swarm Optimization Approaches

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2008 .

On the computation of all global minimizers through particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2004, IEEE Transactions on Evolutionary Computation.

Data preprocessing in predictive data mining

Sotiris B. Kotsiantis, Michael N. Vrahatis, Stamatios-Aggelos N. Alexandropoulos, 2019, The Knowledge Engineering Review.

Solving the linear interval tolerance problem for weight initialization of neural networks

George D. Magoulas, Dimitris A. Karras, Michael N. Vrahatis, 2014, Neural Networks.

Particle Swarm Optimization and Intelligence: Advances and Applications

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2010 .

Applying evolutionary computation methods for the cryptanalysis of Feistel ciphers

Michael N. Vrahatis, Yannis C. Stamatiou, Elena C. Laskari, 2019, Appl. Math. Comput..

Evolutionary adaptation of the differential evolution control parameters

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2009, 2009 IEEE Congress on Evolutionary Computation.

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.

Particle Swarm Optimization Method for Constrained Optimization Problems

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2002 .

Particle swarm optimization for minimax problems

Michael N. Vrahatis, E. C. Laskari, Konstantinos E. Parsopoulos, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

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).

Particle swarm optimization method in multiobjective problems

M. N. Vrahatis, K. E. Parsopoulos, M. N. Vrahatis, 2002, SAC '02.

Particle swarm optimizers for Pareto optimization with enhanced archiving techniques

M.N. Vrahatis, M. N. Vrahatis, P. Limbourg, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Stacking Strong Ensembles of Classifiers

Sotiris B. Kotsiantis, Michael N. Vrahatis, Christos K. Aridas, 2019, AIAI.

Multimodal optimization using niching differential evolution with index-based neighborhoods

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2012, 2012 IEEE Congress on Evolutionary Computation.

Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

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

Evolutionary Operators in Global Optimization with Dynamic Search Trajectories

Michael N. Vrahatis, Elena C. Laskari, Konstantinos E. Parsopoulos, 2003, Numerical Algorithms.

Hybrid local boosting utilizing unlabeled data in classification tasks

Sotiris B. Kotsiantis, Michael N. Vrahatis, Christos K. Aridas, 2017, Evolving Systems.

Combining Prototype Selection with Local Boosting

Sotiris B. Kotsiantis, Michael N. Vrahatis, Christos K. Aridas, 2016, AIAI.

Computational Approaches to Artificial Intelligence: Theory, Methods and Applications

Vassilis P. Plagianakos, Michael N. Vrahatis, G. C. Meletiou, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

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.

Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2010, IEEE Congress on Evolutionary Computation.

Balancing the exploration and exploitation capabilities of the Differential Evolution Algorithm

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Studying the Performance of Unified Particle Swarm Optimization on the Single Machine Total Weighted Tardiness Problem

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2006, Australian Conference on Artificial Intelligence.

Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2012, Inf. Sci..

Studying the Basin of convergence of Methods for Computing periodic orbits

Michael G. Epitropakis, Michael N. Vrahatis, M. N. Vrahatis, 2011, Int. J. Bifurc. Chaos.

Modification of the Particle Swarm Optimizer for Locating All the Global Minima

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2001 .

Hardware-friendly Higher-Order Neural Network Training using Distributed Evolutionary Algorithms

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2010, Appl. Soft Comput..

Existence and computation of short-run equilibria in economic geography

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

A numerical study of the influence of the Poynting-Robertson effect on the equilibrium points of the photogravitational restricted three-body problem II. Out of plane case

M. N. Vrahatis, O. Ragos, F. Zafiropoulos, 1995 .

On the equilibrium points of the relativistic restricted three-body problem

M. N. Vrahatis, O. Ragos, V. Kalantonis, 2001 .

Artificial intelligence methods for music generation: a review and future perspectives

Andreas Floros, Maximos A. Kaliakatsos-Papakostas, Michael N. Vrahatis, 2020 .

Tackling magnetoencephalography with particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, George Dassios, 2009, Int. J. Bio Inspired Comput..

Parameter selection and adaptation in Unified Particle Swarm Optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2007, Math. Comput. Model..

Parallel evolutionary training algorithms for “hardware-friendly” neural networks

Vassilis P. Plagianakos, Michael N. Vrahatis, M. N. Vrahatis, 2002, Natural Computing.

PARTICLE SWARM OPTIMIZATION FOR IMPRECISE PROBLEMS

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2002 .

Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization

Michael N. Vrahatis, Chrysostomos D. Stylios, Elpiniki I. Papageorgiou, 2005, Journal of Intelligent Information Systems.

Fuzzy Cognitive Maps Learning through Swarm Intelligence

Michael N. Vrahatis, Elpiniki I. Papageorgiou, Peter P. Groumpos, 2004, ICAISC.

A first study of fuzzy cognitive maps learning using particle swarm optimization

Michael N. Vrahatis, Peter P. Groumpos, Konstantinos E. Parsopoulos, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

α-Clusterable Sets

Michael N. Vrahatis, Gerasimos Antzoulatos, M. N. Vrahatis, 2011, ECML/PKDD.

On the Complexity of Isolating Real Roots and Computing with Certainty the Topological Degree

Michael N. Vrahatis, Bernard Mourrain, Jean-Claude Yakoubsohn, 2002, J. Complex..

On the Localization and Computation of Zeros of Bessel Functions

Michael N. Vrahatis, O. Ragos, T. N. Grapsa, 1997 .

Locating and Computing Zeros of Airy Functions

Michael N. Vrahatis, O. Ragos, T. N. Grapsa, 1996 .

Algorithm 666: Chabis: a mathematical software package for locating and evaluating roots of systems of nonlinear equations

Michael N. Vrahatis, M. N. Vrahatis, 1988, TOMS.

Solving systems of nonlinear equations using the nonzero value of the topological degree

Michael N. Vrahatis, M. N. Vrahatis, 1988, TOMS.

Efficiently Computing Many Roots of a Function

Michael N. Vrahatis, Dimitris J. Kavvadias, Frosso S. Makri, 2005, SIAM J. Sci. Comput..

The topological degree theory for the localization and computation of complex zeros of bessel functions

Michael N. Vrahatis, O. Ragos, T. N. Grapsa, 1997 .

Finding multiple global optima exploiting differential evolution's niching capability

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2011, 2011 IEEE Symposium on Differential Evolution (SDE).

Interactive music composition driven by feature evolution

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2016, SpringerPlus.

Dynamic search trajectory methods for global optimization

Stamatios-Aggelos N. Alexandropoulos, M. N. Vrahatis, P. Pardalos, 2019, Annals of Mathematics and Artificial Intelligence.

Analysis of epileptic magnetoencephalogram dynamics through clustering algorithms

Michael N. Vrahatis, Adam Adamopoulos, Basilis Boutsinas, 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

Hybrid methods using evolutionary algorithms for on-line training

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Globally Convergent Modification of the Quickprop Method

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2000, Neural Processing Letters.

Effective Backpropagation Training with Variable Stepsize

George D. Magoulas, Michael N. Vrahatis, George S. Androulakis, 1997, Neural Networks.

Training multilayer networks with discrete activation functions

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Intelligent Real-Time Music Accompaniment for Constraint-Free Improvisation

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

Investigating the existence of function roots using particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Improved Learning of Neural Nets Through Global Search

Vassilis P. Plagianakos, Michael N. Vrahatis, George D. Magoulas, 2006 .

TRACING PERIODIC ORBITS IN 3D GALACTIC POTENTIALS BY THE PARTICLE SWARM OPTIMIZATION METHOD

M. N. Vrahatis, K. Parsopoulos, P. Patsis, 2005 .

Searching for the Optimal Defence Expenditure

M. N. Vrahatis, K. Parsopoulos, G. Zombanakis, 2002 .

Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods

George D. Magoulas, Michael N. Vrahatis, George S. Androulakis, 1999, Neural Computation.

Novel orbit based symmetric cryptosystems

Michael N. Vrahatis, Elena C. Laskari, Georgios A. Tsirogiannis, 2010, Math. Comput. Model..

Neural network-based colonoscopic diagnosis using on-line learning and differential evolution

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2004, Appl. Soft Comput..

Unsupervised Clustering Using Semi-Algebraic Data Structures

Michael N. Vrahatis, D. K. Tasoulis, M. N. Vrahatis, 2019, International Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004).

A technique for the visualization of population-based algorithms

Michael N. Vrahatis, Voula C. Georgopoulos, Konstantinos E. Parsopoulos, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Deflation techniques for the determination of periodic solutions of a certain period

M. N. Vrahatis, O. Ragos, V. Kalantonis, 2003 .

On the application of optimization methods to the determination of members of families of periodic solutions

M. N. Vrahatis, O. Ragos, V. Kalantonis, 2003 .

Computing periodic orbits of nondifferentiable/discontinuous mappings through particle swarm optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

Efficient Method for Computing with Certainty Periodic Orbits on a Surface of Section

Michael N. Vrahatis, M. N. Vrahatis, E. A. Perdios, 2002 .

Computing families of periodic orbits through optimization methods

M. N. Vrahatis, G. Androulakis, O. Ragos, 2001 .

Geometry of learning: visualizing the performance of neural network supervised training methods

Michael N. Vrahatis, George D. Magoulas, M. N. Vrahatis, 1997 .

PERIODIC ORBITS AND INVARIANT SURFACES OF 4D NONLINEAR MAPPINGS

Michael N. Vrahatis, M. N. Vrahatis, Tassos Bountis, 1996 .

An efficient method for locating and computing periodic orbits of nonlinear mappings

Michael N. Vrahatis, M. N. Vrahatis, 1995 .

A new ensemble method for outlier identification

Sotiris B. Kotsiantis, Michael N. Vrahatis, Stamatios-Aggelos N. Alexandropoulos, 2020, 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence).

Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network

Sotiris B. Kotsiantis, Michael N. Vrahatis, Stamatios-Aggelos N. Alexandropoulos, 2019, 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA).

Integrating global and local boosting

Michael N. Vrahatis, Sotiris Kotsiantis, Anastasia-Dimitra Lipitakis, 2015, 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA).

Feature Extraction Using Pitch Class Profile Information Entropy

Michael G. Epitropakis, Michael N. Vrahatis, Maximos A. Kaliakatsos-Papakostas, 2011, MCM.

Weighted Markov Chain Model for Musical Composer Identification

Michael G. Epitropakis, Michael N. Vrahatis, Maximos A. Kaliakatsos-Papakostas, 2011, EvoApplications.

The New k-Windows Algorithm for Improving the k-Means Clustering Algorithm

Michael N. Vrahatis, Georgios Pavlides, Basilis Boutsinas, 2002, J. Complex..

Learning Rate Adaptation in Stochastic Gradient Descent

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2001 .

Nonmonotone methods for backpropagation training with adaptive learning rate

George D. Magoulas, Michael N. Vrahatis, M. N. Vrahatis, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Evolutionary Methods for the Approximation of the Stability Domain and Frequency Optimization of Conservative Maps

Michael N. Vrahatis, Tassos Bountis, Yiannis G. Petalas, 2008, Int. J. Bifurc. Chaos.

Computing nash equilibria through particle swarm optimization

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

Unified Particle Swarm Optimization in Dynamic Environments

Michael N. Vrahatis, Konstantinos E. Parsopoulos, M. N. Vrahatis, 2005, EvoWorkshops.

Recent approaches to global optimization problems through Particle Swarm Optimization

M. N. Vrahatis, K. Parsopoulos, M. Vrahatis, 2002, Natural Computing.

Ant-Based Approaches for Solving Autocorrelation Problems

Michael N. Vrahatis, Ilias S. Kotsireas, Konstantinos E. Parsopoulos, 2012, ANTS.

Improved sign-based learning algorithm derived by the composite nonlinear Jacobi process

Michael N. Vrahatis, George D. Magoulas, Aristoklis D. Anastasiadis, 2006 .

Computational Intelligence Methods for Financial Time Series Modeling

M. N. Vrahatis, N. Pavlidis, V. Plagianakos, 2006, Int. J. Bifurc. Chaos.

Evolutionary training of hardware realizable multilayer perceptrons

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2006, Neural Computing & Applications.

Sign-based learning schemes for pattern classification

George D. Magoulas, Michael N. Vrahatis, Aristoklis D. Anastasiadis, 2005, Pattern Recognit. Lett..

Deterministic nonmonotone strategies for effective training of multilayer perceptrons

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2002, IEEE Trans. Neural Networks.

Globally convergent algorithms with local learning rates

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2002, IEEE Trans. Neural Networks.

Effective neural network training with a different learning rate for each weight

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

Nonmonotone learning rules for backpropagation networks

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

On the alleviation of the problem of local minima in back-propagation

Michael N. Vrahatis, George D. Magoulas, M. N. Vrahatis, 1997 .

Improved Neural Network-based Interpretation of Colonoscopy Images Through On-line Learning and Evolution

Vassilis P. Plagianakos, Michael N. Vrahatis, George D. Magoulas, 2001 .

A framework for the development of globally convergent adaptive learning rate algorithms

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2001 .

SUPERVISED TRAINING USING GLOBAL SEARCH METHODS

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2001 .

A Nonmonotone Backpropagation Training Method for Neural Networks

Vassilis P. Plagianakos, Michael N. Vrahatis, D. G. Sotiropoulos, 1998 .

TRAJECTORY METHODS FOR SUPERVISED LEARNING

Michael N. Vrahatis, M. N. Vrahatis, Y. G. Petalas, 2022 .

Parallelizing the Unsupervised k-Windows Clustering Algorithm

Dimitris K. Tasoulis, Michael N. Vrahatis, Panagiotis D. Alevizos, 2003, PPAM.

Improving the orthogonal range search k-windows algorithm

Dimitris K. Tasoulis, Michael N. Vrahatis, Basilis Boutsinas, 2002, 14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings..

Particle Swarm Optimization for Computing Nash and Stackelberg Equilibria in Energy Markets

Michael N. Vrahatis, Panagiotis Kontogiorgos, George P. Papavassilopoulos, 2020, SN Operations Research Forum.

Improving fuzzy cognitive maps learning through memetic particle swarm optimization

M. N. Vrahatis, Y. G. Petalas, K. Parsopoulos, 2008, Soft Comput..

Particle filtering with particle swarm optimization in systems with multiplicative noise

Michael N. Vrahatis, Konstantinos E. Parsopoulos, A. D. Klamargias, 2008, GECCO '08.

Particle Swarm Optimization for Tackling Continuous Review Inventory Models

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Konstantina Skouri, 2008, EvoWorkshops.

Root finding and approximation approaches through neural networks

Michael G. Epitropakis, Michael N. Vrahatis, M. N. Vrahatis, 2005, SIGS.

Evolutionary Algorithm Training of Higher Order Neural Networks

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2010 .

Improving the Particle Swarm Optimizer by Function “Stretching”

Vassilis P. Plagianakos, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2001 .

Training neural networks with threshold activation functions and constrained integer weights

Vassilis P. Plagianakos, Michael N. Vrahatis, M. N. Vrahatis, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Hybrid local boosting utilizing unlabeled data in classification tasks

Christos K. Aridas, M. N. Vrahatis, S. Kotsiantis, 2019, Evol. Syst..

A short proof and a generalization of Miranda’s existence theorem

Michael N. Vrahatis, M. N. Vrahatis, M. Vrahatis, 1989 .

Sign-methods for training with imprecise error function and gradient values

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Development and convergence analysis of training algorithms with local learning rate adaptation

V.P. Plagianakos, G.D. Magoulas, M.N. Vrahatis, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Performance evaluation of clustering algorithms on microcalcifications as mammography findings

Michael N. Vrahatis, George M. Spyrou, Panos A. Ligomenides, 2013, 13th IEEE International Conference on BioInformatics and BioEngineering.