Michael N. Vrahatis

发表

Evolutionary Algorithm Training of Higher Order Neural Networks

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

Data mining and cryptology

Dimitris K. Tasoulis, Michael N. Vrahatis, E. C. Laskari, 2003 .

Design and Analysis of Optimization Algorithms Using Computational Statistics

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

Aitken and Neville inverse interpolation methods for the Lucas logarithm problem

Michael N. Vrahatis, Elena C. Laskari, Gerasimos C. Meletiou, 2009, Appl. Math. Comput..

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).

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.

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.

UNSUPERVISED CLUSTER ANALYSIS IN BIOINFORMATICS

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

Combining Prototype Selection with Local Boosting

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

Revisiting the Problem of Weight Initialization for Multi-Layer Perceptrons Trained with Back Propagation

Dimitris A. Karras, Michael N. Vrahatis, Stavros P. Adam, 2008, ICONIP.

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).

Locally recurrent probabilistic neural network for text-independent speaker verification

Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis, 2003, INTERSPEECH.

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.

Globally convergent algorithms with local learning rates

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

Ant-Based Approaches for Solving Autocorrelation Problems

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

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).

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

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

Parameter selection and adaptation in Unified Particle Swarm Optimization

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

Multi-Objective Particles Swarm Optimization Approaches

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

Partially Connected Locally Recurrent Probabilistic Neural Networks

Todor Ganchev, Michael N. Vrahatis, Nikos Fakotakis, 2008 .

Locating and Computing Arbitrarily Distributed Zeros

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

Non-monotone differential evolution

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2008, GECCO '08.

Improving the Particle Swarm Optimizer by Function “Stretching”

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

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..

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.

Direct Zero-Norm Minimization for Neural Network Pruning and Training

George D. Magoulas, Michael N. Vrahatis, Stavros P. Adam, 2012, EANN.

Evolutionary Algorithms for Integer Weight Neural Network Training

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

Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization

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

Real-time drums transcription with characteristic bandpass filtering

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012, AM '12.

PARTICLE SWARM OPTIMIZATION FOR IMPRECISE PROBLEMS

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

Artificial nonmonotonic neural networks

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

A Study on Clustering Initial Weights Space of MLP Neural Networks in Terms of Fast Convergence and Generalization Capability

Michael N. Vrahatis, D. A. Karras, Stavros P. Adam, 2019 .

Automated Horizontal Orchestration Based on Multichannel Musical Recordings

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012 .

Memetic particle swarm optimization

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

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).

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.

Evolutionary training of hardware realizable multilayer perceptrons

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

Recognizing predictive patterns in chaotic maps

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

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).

Transformations of Cryptographic Schemes Through Interpolation Techniques

Michael N. Vrahatis, G. C. Meletiou, Stamatios-Aggelos N. Alexandropoulos, 2015 .

Determining the number of real roots of polynomials through neural networks

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

Chaos and Music: from Time Series Analysis to Evolutionary Composition

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

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.

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..

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.

Analysis of Particle Swarm Optimization Using Computational Statistics

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

Differential Evolution Algorithms for Finding Predictive Gene Subsets in Microarray Data

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

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

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

Designing particle swarm optimization with regression trees

Thomas Bartz-Beielstein, Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2004 .

Unsupervised clustering on dynamic databases

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

Root finding and approximation approaches through neural networks

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

Oriented k-windows: A PCA driven clustering method

Dimitris K. Tasoulis, Michael N. Vrahatis, Efstratios Gallopoulos, 2006, Advances in Web Intelligence and Data Mining.

Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems

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

Genetic evolution of L and FL-systems for the production of rhythmic sequences

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012, GECCO '12.

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.

Particle filtering with particle swarm optimization in systems with multiplicative noise

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

Learning Rate Adaptation in Stochastic Gradient Descent

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

Recent approaches to global optimization problems through Particle Swarm Optimization

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

Parallelizing the Unsupervised k-Windows Clustering Algorithm

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

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.

Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks

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

Online Neural Network Training for Automatic Ischemia Episode Detection

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

Integer weight training by differential evolution algorithms

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

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..

Automatic Adaptation of Learning Rate for Backpropagation Neural Networks

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

Solving systems of nonlinear equations In using a rotating hyperplane in

Michael N. Vrahatis, Tassos Bountis, Theodoula N. Grapsa, 1990, Int. J. Comput. Math..

Privacy Preserving Unsupervised Clustering over Vertically Partitioned Data

Dimitris K. Tasoulis, Michael N. Vrahatis, Elena C. Laskari, 2006, ICCSA.

Reliable estimation of a neural network's domain of validity through interval analysis based inversion

George D. Magoulas, Dimitris A. Karras, Michael N. Vrahatis, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Multi-Objective Particles Swarm Optimization Approaches

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

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.

Deterministic nonmonotone strategies for effective training of multilayer perceptrons

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

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).

An Efficient Method for Computing Periodic Orbits of Conservative Dynamical Systems

Michael N. Vrahatis, Tassos Bountis, T. Bountis, 1994 .

Tuning PSO Parameters Through Sensitivity Analysis

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

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..

Tumor detection in colonoscopic images using hybrid methods for on-line neural network training

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

Improved Learning of Neural Nets Through Global Search

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

Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems

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

Unsupervised distributed clustering

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

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..

SUPERVISED TRAINING USING GLOBAL SEARCH METHODS

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

A class of adaptive learning rate algorithms derived by one-dimensional subminimization methods

George D. Magoulas, Michael N. Vrahatis, 2000, Neural Parallel Sci. Comput..

Fuzzy Evolutionary Probabilistic Neural Networks

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

p-MEMPSODE: Parallel and irregular memetic global optimization

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

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

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

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.

Computational Intelligence Algorithms and DNA Microarrays

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

Novel orbit based symmetric cryptosystems

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

Algorithm 987

Michael N. Vrahatis, Dimitris J. Kavvadias, Frosso S. Makri, 2018, ACM Trans. Math. Softw..

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

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

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).

Privacy preserving electronic data gathering

Dimitris K. Tasoulis, Michael N. Vrahatis, Elena C. Laskari, 2005, Math. Comput. Model..

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

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

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

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

A Globally Convergent Jacobi-Bisection Method for Neural Network Training

Michael N. Vrahatis, George D. Magoulas, Aristoklis D. Anastasiadis, 2019 .

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).

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.

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.

Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

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

An e-voting-based data gathering scheme for decision support systems

Michael N. Vrahatis, G. C. Meletiou, V. I. Galanis, 2010 .

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).

Locating, characterizing and computing the stationary points of a function

Michael N. Vrahatis, Evangelia Triantafyllou, 1996, Reliab. Comput..

Distributed computing methodology for training neural networks in an image-guided diagnostic application

George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis, 2006, Comput. Methods Programs Biomed..

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.

Evolutionary Bayesian Probabilistic Neural Networks

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

An Improved Backpropagation Method with Adaptive Learning Rate

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

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.

Increasing Diversity in Random Forests Using Naive Bayes

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

Cryptography and Cryptanalysis Through Computational Intelligence

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

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).

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

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

Additional Referees

Ioannis Stamelos, Yannis Avrithis, Georgios Dounias, 2005, ITCC.

A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World Tasks

Dimitris A. Karras, Michael N. Vrahatis, Stavros P. Adam, 2009, Industrial Conference on Data Mining - Posters.

Computational Intelligence Methods for Financial Time Series Modeling

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

A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm

George D. Magoulas, Michael N. Vrahatis, Aristoklis D. Anastasiadis, 2004, ESANN.

10 Intelligent Music Composition

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

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).

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.

Particle Swarm Optimization for Tackling Continuous Review Inventory Models

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

Locally Recurrent Probabilistic Neural Networks with Application to Speaker Verification

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

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.

Feature Extraction Using Pitch Class Profile Information Entropy

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

Comparison study of textural descriptors for training neural network classifiers

George D. Magoulas, Michael N. Vrahatis, D. A. Karras, 1999 .

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..

Globally Convergent Modification of the Quickprop Method

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

A training method for discrete multilayer neural networks

George D. Magoulas, Michael N. Vrahatis, G. S. Androulakis, 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).

Unsupervised Clustering Using Fractal Dimension

Dimitris K. Tasoulis, Michael N. Vrahatis, 2006, Int. J. Bifurc. Chaos.

Assessing the effectiveness of artificial neural networks on problems related to elliptic curve cryptography

Dimitris K. Tasoulis, Michael N. Vrahatis, Yannis C. Stamatiou, 2007, Math. Comput. Model..

Evaluating generalization through interval-based neural network inversion

Michael N. Vrahatis, Stavros P. Adam, Aristidis C. Likas, 2019, Neural Computing and Applications.

Optimal Dynamic Box-Counting Algorithm

Michael N. Vrahatis, Panagiotis D. Alevizos, M. Vrahatis, 2010, Int. J. Bifurc. Chaos.

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).

Controlling interactive evolution of 8-bit melodies with genetic programming

Michael G. Epitropakis, Michael N. Vrahatis, Andreas Floros, 2012, Soft Computing.

Unsupervised clustering in mRNA expression profiles

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

Parallel Unsupervised k-Windows: An Efficient Parallel Clustering Algorithm

Dimitris K. Tasoulis, Michael N. Vrahatis, Basilis Boutsinas, 2003, PaCT.

On perturbation of roots of homogeneous algebraic systems

Michael N. Vrahatis, Susumu Tanabé, S. Tanabé, 2006, Math. Comput..

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.

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

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

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

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

Improving fuzzy cognitive maps learning through memetic particle swarm optimization

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

Optimizing the Performance of Probabilistic Neural Networks in a BioinformaticsTa sk

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

Evolutionary Operators in Global Optimization with Dynamic Search Trajectories

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

A Clustering Strategy for the Key Segmentation of Musical Audio

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

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

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

No Free Lunch Theorem: A Review

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

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

Michael N. Vrahatis, Theodoula N. Grapsa, 1995, Int. J. Comput. Math..

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.

Intelligent Generation of Rhythmic Sequences Using Finite L-systems

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

A Method for Computing Families of Periodic Orbits Based on Unconstrained Optimization

Michael N. Vrahatis, O. Ragos, G. S. Androulakis, 1999 .

Music Synthesis Based on Nonlinear Dynamics

Michael N. Vrahatis, Andreas Floros, Maximos A. Kaliakatsos-Papakostas, 2012 .

evoDrummer: Deriving Rhythmic Patterns through Interactive Genetic Algorithms

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

PVM-based training of large neural architectures

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

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.

A Deep Dense Neural Network for Bankruptcy Prediction

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

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).

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.

Content driven clustering algorithm combining density and distance functions

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

Stacking Strong Ensembles of Classifiers

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

Applying evolutionary computation methods for the cryptanalysis of Feistel ciphers

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

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.

Data preprocessing in predictive data mining

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

New globally convergent training scheme based on the resilient propagation algorithm

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

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

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

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).

Enhanced Learning inFuzzySimulation Models Using MemeticParticle Swarm Optimization

Michael N. Vrahatis, Konstantinos E. Parsopoulos, Elpiniki I. Papageorgiou, 2007 .

Hybrid local boosting utilizing unlabeled data in classification tasks

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

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..

Unsupervised Clustering of Bioinformatics Data

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

A Review of Major Application Areas of Differential Evolution

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

Locating and Computing All the Simple Roots and Extrema of a Function

Michael N. Vrahatis, Dimitris J. Kavvadias, D. Kavvadias, 1996, SIAM J. Sci. Comput..

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.

Convergence analysis of the Quickprop method

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

Cryptography , Network Security and Applications in the Armed Forces

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

Neural network training with constrained integer weights

Vassilis P. Plagianakos, Michael N. Vrahatis, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

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).

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..

Trajectory Methods for Neural Network Training

Michael N. Vrahatis, Y. G. Petalas, 2003 .

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).

Memetic Algorithms for Neural Network Training in Bioinformatics

Michael N. Vrahatis, Y. G. Petalas, 2004 .

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.

Unified Particle Swarm Optimization in Dynamic Environments

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

Weighted Markov Chain Model for Musical Composer Identification

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

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

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

Computational intelligence algorithms for risk-adjusted trading strategies

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

Higher-Order Neural Networks Training Using Differential Evolution

Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis, 2006 .

Effective Backpropagation Training with Variable Stepsize

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

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

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

Dynamic Search Trajectory Methods for Neural Network Training

Dimitris K. Tasoulis, Michael N. Vrahatis, Yiannis G. Petalas, 2004, ICAISC.

A new method in neural network supervised training with imprecision

George D. Magoulas, Michael N. Vrahatis, G. S. Androulakis, 1996, Proceedings of Third International Conference on Electronics, Circuits, and Systems.

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.

Sign-based learning schemes for pattern classification

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

Particle Swarm Optimization: An efficient method for tracing periodic orbits in 3D galactic potentials pdf

Michael N. Vrahatis, Konstantinos E. Parsopoulos, P. A. Patsis, 2005, ArXiv.

Fuzzy Cognitive Maps Learning through Swarm Intelligence

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

Interval Analysis Based Neural Network Inversion: A Means for Evaluating Generalization

Michael N. Vrahatis, Stavros P. Adam, A. C. Likas, 2017, EANN.

Nonlinear Optimization Approaches for Training Neural Networks

Vassilis P. Plagianakos, Michael N. Vrahatis, George D. Magoulas, 2015 .

Particle Swarm Optimization Method for Constrained Optimization Problems

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

Evolutionary adaptation of the differential evolution control parameters

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

Efficiently Computing Many Roots of a Function

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

A note on a secure voting system on a public network

Michael N. Vrahatis, Gerasimos C. Meletiou, M. G. Karagiannopoulos, 2004, Networks.

Financial forecasting through unsupervised clustering and neural networks

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

Tackling magnetoencephalography with particle swarm optimization

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

Generalizing the k-Windows clustering algorithm in metric spaces

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

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).

α-Clusterable Sets

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

Transformations of two cryptographic problems in terms of matrices

Dimitris K. Tasoulis, Michael N. Vrahatis, Elena C. Laskari, 2005, SIGS.

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..

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

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

Musical Composer Identification through Probabilistic and Feedforward Neural Networks

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

Particle Swarm Optimization and Intelligence: Advances and Applications

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

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.

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).

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).

Interactive music composition driven by feature evolution

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

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.

A Nonmonotone Backpropagation Training Method for Neural Networks

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

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

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

Deflection and Stretching Techniques for Detection of Multiple Minimizers in Multimodal Optimization Problems

Michael N. Vrahatis, Konstantinos E. Parsopoulos, 2021 .

Computational insights on the molecular mechanisms across breast cancer progression combining gene differential expression and co-expression

Michael N. Vrahatis, George M. Spyrou, George Kolios, 2021, 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI).

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 .

A procedure to compute the fixed points and visualize the orbits of a 2D map

Michael N. Vrahatis, Giorgio Turchetti, G. Servizi, 1993 .

Locating and Computing Zeros of Airy Functions

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

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

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

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

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

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

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

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

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

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

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

A convergence-improving iterative method for computing periodic orbits near Bifurcation Points

Michael N. Vrahatis, Tassos Bountis, T. Bountis, 1990 .

Sign Methods for Enumerating Solutions of Nonlinear Algebraic Systems

Michael N. Vrahatis, Bernard Mourrain, Ioannis Z. Emiris, 2001 .

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

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

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).

The implicit function theorem for solving systems of nonlinear equations in

Michael N. Vrahatis, T. N. Grapsa, 1989 .

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

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

Cryptography through Interpolation, Approximation and Computational Intelligence Methods

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

An Efficient Improvement of the Rprop Algorithm

George D. Magoulas, Michael N. Vrahatis, Aristoklis D. Anastasiadis, 2003 .

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..

Detecting resonances in conservative maps using evolutionary algorithms

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

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

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

PERIODIC ORBITS AND INVARIANT SURFACES OF 4D NONLINEAR MAPPINGS

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

Topological degree theory and local analysis of area preserving maps

Michael N. Vrahatis, Giorgio Turchetti, G. Servizi, 2003 .

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

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

Computing the Number of Real Roots of Polynomials through Neural Networks

Dimitris K. Tasoulis, Nicos G. Pavlidis, 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 .

EXCHANGE RATE FORECASTING THROUGH DISTRIBUTED TIME-LAGGED FEEDFORWARD NEURAL NETWORKS

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

Matrix representation of cryptographic functions

Dimitris K. Tasoulis, Michael N. Vrahatis, E. C. Laskari, 2013 .

Giotto:. a Code for the Nonlinear Analysis of Area-Preserving Mappings

Ezio Todesco, Michael N. Vrahatis, Massimo Giovannozzi, 1995 .

Neural network supervised training based on a dimension reducing method

George D. Magoulas, Michael N. Vrahatis, T. N. Grapsa, 1997 .

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 .

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

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

Computing nash equilibria through particle swarm optimization

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

Studying the performance of optimization methods by visualization

Michael N. Vrahatis, T. N. Grapsa, G. S. Androulakis, 1996 .

Learning in multilayer perceptrons using global optimization strategies

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

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

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

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

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

A dimension-reducing method for unconstrained optimization

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

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).

TRAJECTORY METHODS FOR SUPERVISED LEARNING

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

On the Localization and Computation of Zeros of Bessel Functions

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

RECENT APPROACHES TO ELECTRONIC DATA GATHERING WITH PRIVACY

Michael N. Vrahatis, Elena C. Laskari, Gerasimos C. Meletiou, 2004 .

SMALLER ALIGNMENT INDEX ( SALI ) : DETECTING ORDER AND CHAOS IN CONSERVATIVE DYNAMICAL SYSTEMS

Michael N. Vrahatis, Charalampos Skokos, C. Antonopoulos, 2002 .

Analysis of Normal and Pathological Fetal Magnetocardiograms Using Clustering Algorithms

Michael N. Vrahatis, Adam Adamopoulos, Basilis Boutsinas, 2001 .

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 .

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

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

Aitken and Neville Inverse Interpolation Methods over Finite Fields

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