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Michael N. Vrahatis
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Journal Articles
- 2023
- [j77]Athanasios I. Salamanis, George A. Gravvanis, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Novel Sparse Feature Regression Method for Traffic Forecasting. Int. J. Artif. Intell. Tools 32(1): 2350008:1-2350008:27 (2023) - 2022
- [j76]Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, George A. Gravvanis, Michael N. Vrahatis:
Rotation forest of random subspace models. Intell. Decis. Technol. 16(2): 315-324 (2022) - 2020
- [j75]Stamatios-Aggelos N. Alexandropoulos, Panos M. Pardalos, Michael N. Vrahatis:
Dynamic search trajectory methods for global optimization. Ann. Math. Artif. Intell. 88(1-3): 3-37 (2020) - [j74]Michael N. Vrahatis, Panagiotis Kontogiorgos, George P. Papavassilopoulos:
Particle Swarm Optimization for Computing Nash and Stackelberg Equilibria in Energy Markets. Oper. Res. Forum 1(3) (2020) - 2019
- [j73]Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Hybrid local boosting utilizing unlabeled data in classification tasks. Evol. Syst. 10(1): 51-61 (2019) - [j72]Nikolay T. Dukov, Todor D. Ganchev, Michael N. Vrahatis:
Evaluation of PNN pattern-layer activation function approximations in different training setups. Int. J. Speech Technol. 22(4): 1039-1049 (2019) - [j71]Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Data preprocessing in predictive data mining. Knowl. Eng. Rev. 34: e1 (2019) - [j70]Stavros P. Adam, Aristidis C. Likas, Michael N. Vrahatis:
Evaluating generalization through interval-based neural network inversion. Neural Comput. Appl. 31(12): 9241-9260 (2019) - [j69]Emmanouil K. Ikonomakis, George M. Spyrou, Michael N. Vrahatis:
Content driven clustering algorithm combining density and distance functions. Pattern Recognit. 87: 190-202 (2019) - 2018
- [j68]Dimitra-Nefeli A. Zottou, Dimitris J. Kavvadias, Frosso S. Makri, Michael N. Vrahatis:
Algorithm 987: MANBIS - A C++ Mathematical Software Package for Locating and Computing Efficiently Many Roots of a Function: Theoretical Issues. ACM Trans. Math. Softw. 44(3): 35:1-35:7 (2018) - 2016
- [j67]Stavros P. Adam, George D. Magoulas, Dimitrios A. Karras, Michael N. Vrahatis:
Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach. J. Mach. Learn. Res. 17: 169:1-169:40 (2016) - 2015
- [j66]Constantinos Voglis, Panagiotis E. Hadjidoukas, Konstantinos E. Parsopoulos, Dimitris G. Papageorgiou, Isaac E. Lagaris, Michael N. Vrahatis:
p-MEMPSODE: Parallel and irregular memetic global optimization. Comput. Phys. Commun. 197: 190-211 (2015) - 2014
- [j65]Stavros P. Adam, Dimitrios A. Karras, George D. Magoulas, Michael N. Vrahatis:
Solving the linear interval tolerance problem for weight initialization of neural networks. Neural Networks 54: 17-37 (2014) - 2013
- [j64]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Michael N. Vrahatis:
A Clustering Strategy for the Key Segmentation of Musical Audio. Comput. Music. J. 37(1): 52-69 (2013) - [j63]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Andreas Floros, Michael N. Vrahatis:
Chaos and Music: from Time Series Analysis to Evolutionary Composition. Int. J. Bifurc. Chaos 23(11) (2013) - 2012
- [j62]Constantinos Voglis, Konstantinos E. Parsopoulos, Dimitris G. Papageorgiou, Isaac E. Lagaris, Michael N. Vrahatis:
MEMPSODE: A global optimization software based on hybridization of population-based algorithms and local searches. Comput. Phys. Commun. 183(5): 1139-1154 (2012) - [j61]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach. Inf. Sci. 216: 50-92 (2012) - [j60]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Andreas Floros, Michael N. Vrahatis:
Controlling interactive evolution of 8-bit melodies with genetic programming. Soft Comput. 16(12): 1997-2008 (2012) - 2011
- [j59]Michael G. Epitropakis, Michael N. Vrahatis:
Studying the Basin of convergence of Methods for Computing periodic orbits. Int. J. Bifurc. Chaos 21(8): 2079-2106 (2011) - [j58]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators. IEEE Trans. Evol. Comput. 15(1): 99-119 (2011) - 2010
- [j57]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Hardware-friendly Higher-Order Neural Network Training using Distributed Evolutionary Algorithms. Appl. Soft Comput. 10(2): 398-408 (2010) - [j56]Panagiotis D. Alevizos, Michael N. Vrahatis:
Optimal Dynamic Box-Counting Algorithm. Int. J. Bifurc. Chaos 20(12): 4067-4077 (2010) - [j55]Adam V. Adamopoulos, Nicos G. Pavlidis, Michael N. Vrahatis:
Evolving cellular automata rules for multiple-step-ahead prediction of complex binary sequences. Math. Comput. Model. 51(3-4): 229-238 (2010) - [j54]Michael N. Vrahatis, Georgios A. Tsirogiannis, Elena C. Laskari:
Novel orbit based symmetric cryptosystems. Math. Comput. Model. 51(3-4): 239-246 (2010) - 2009
- [j53]Elena C. Laskari, Gerasimos C. Meletiou, Michael N. Vrahatis:
Aitken and Neville inverse interpolation methods for the Lucas logarithm problem. Appl. Math. Comput. 209(1): 52-56 (2009) - [j52]Konstantinos E. Parsopoulos, Fotini Kariotou, George Dassios, Michael N. Vrahatis:
Tackling magnetoencephalography with particle swarm optimization. Int. J. Bio Inspired Comput. 1(1/2): 32-49 (2009) - [j51]Yiannis G. Petalas, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Improving fuzzy cognitive maps learning through memetic particle swarm optimization. Soft Comput. 13(1): 77-94 (2009) - 2008
- [j50]Yiannis G. Petalas, Chris G. Antonopoulos, Tassos Bountis, Michael N. Vrahatis:
Evolutionary Methods for the Approximation of the Stability Domain and Frequency Optimization of Conservative Maps. Int. J. Bifurc. Chaos 18(8): 2249-2264 (2008) - [j49]Vasileios L. Georgiou, Philipos D. Alevizos, Michael N. Vrahatis:
Novel Approaches to Probabilistic Neural Networks Through Bagging and Evolutionary Estimating of Prior Probabilities. Neural Process. Lett. 27(2): 153-162 (2008) - 2007
- [j48]Elena C. Laskari, Gerasimos C. Meletiou, Yannis C. Stamatiou, Michael N. Vrahatis:
Applying evolutionary computation methods for the cryptanalysis of Feistel ciphers. Appl. Math. Comput. 184(1): 63-72 (2007) - [j47]Nicos G. Pavlidis, Michael N. Vrahatis, Pascal Mossay:
Existence and computation of short-run equilibria in economic geography. Appl. Math. Comput. 184(1): 93-103 (2007) - [j46]Yiannis G. Petalas, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Memetic particle swarm optimization. Ann. Oper. Res. 156(1): 99-127 (2007) - [j45]Todor Ganchev, Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis:
Generalized locally recurrent probabilistic neural networks with application to text-independent speaker verification. Neurocomputing 70(7-9): 1424-1438 (2007) - [j44]Elena C. Laskari, Gerasimos C. Meletiou, Yannis C. Stamatiou, Dimitris K. Tasoulis, Michael N. Vrahatis:
Assessing the effectiveness of artificial neural networks on problems related to elliptic curve cryptography. Math. Comput. Model. 46(1-2): 174-179 (2007) - [j43]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Parameter selection and adaptation in Unified Particle Swarm Optimization. Math. Comput. Model. 46(1-2): 198-213 (2007) - [j42]Dimitris K. Tasoulis, Michael N. Vrahatis:
Generalizing the k-Windows clustering algorithm in metric spaces. Math. Comput. Model. 46(1-2): 268-277 (2007) - 2006
- [j41]Dimitris K. Tasoulis, Panagiota Spyridonos, Nicos G. Pavlidis, Vassilis P. Plagianakos, Panagiota Ravazoula, George Nikiforidis, Michael N. Vrahatis:
Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence. Artif. Intell. Medicine 38(3): 291-303 (2006) - [j40]Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Unsupervised clustering in mRNA expression profiles. Comput. Biol. Medicine 36(10): 1126-1142 (2006) - [j39]Bernard Mourrain, Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Determining the number of real roots of polynomials through neural networks. Comput. Math. Appl. 51(3-4): 527-536 (2006) - [j38]Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis:
Distributed computing methodology for training neural networks in an image-guided diagnostic application. Comput. Methods Programs Biomed. 81(3): 228-235 (2006) - [j37]Vasileios L. Georgiou, Nicos G. Pavlidis, Konstantinos E. Parsopoulos, Philipos D. Alevizos, Michael N. Vrahatis:
New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks. Int. J. Artif. Intell. Tools 15(3): 371-396 (2006) - [j36]George D. Magoulas, Michael N. Vrahatis:
Adaptive Algorithms for Neural Network Supervised Learning: a Deterministic Optimization Approach. Int. J. Bifurc. Chaos 16(7): 1929-1950 (2006) - [j35]Nicos G. Pavlidis, Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Computational Intelligence Methods for Financial Time Series Modeling. Int. J. Bifurc. Chaos 16(7): 2053-2062 (2006) - [j34]Dimitris K. Tasoulis, Michael N. Vrahatis:
Unsupervised Clustering Using Fractal Dimension. Int. J. Bifurc. Chaos 16(7): 2073-2079 (2006) - [j33]Susumu Tanabé, Michael N. Vrahatis:
On perturbation of roots of homogeneous algebraic systems. Math. Comput. 75(255): 1383-1402 (2006) - [j32]Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis:
Evolutionary training of hardware realizable multilayer perceptrons. Neural Comput. Appl. 15(1): 33-40 (2006) - [j31]Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis:
Financial forecasting through unsupervised clustering and neural networks. Oper. Res. 6(2): 103-127 (2006) - 2005
- [j30]Michael G. Epitropakis, Michael N. Vrahatis:
Root finding and approximation approaches through neural networks. SIGSAM Bull. 39(4): 118-121 (2005) - [j29]Elena C. Laskari, Gerasimos C. Meletiou, Dimitris K. Tasoulis, Michael N. Vrahatis:
Transformations of two cryptographic problems in terms of matrices. SIGSAM Bull. 39(4): 127-130 (2005) - [j28]Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis:
New globally convergent training scheme based on the resilient propagation algorithm. Neurocomputing 64: 253-270 (2005) - [j27]Elpiniki Papageorgiou, Konstantinos E. Parsopoulos, Chrysostomos D. Stylios, Petros P. Groumpos, Michael N. Vrahatis:
Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization. J. Intell. Inf. Syst. 25(1): 95-121 (2005) - [j26]Elena C. Laskari, Gerasimos C. Meletiou, Dimitris K. Tasoulis, Michael N. Vrahatis:
Privacy preserving electronic data gathering. Math. Comput. Model. 42(7-8): 739-746 (2005) - [j25]Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis:
Sign-based learning schemes for pattern classification. Pattern Recognit. Lett. 26(12): 1926-1936 (2005) - [j24]Dimitris K. Tasoulis, Michael N. Vrahatis:
Unsupervised clustering on dynamic databases. Pattern Recognit. Lett. 26(13): 2116-2127 (2005) - [j23]Dimitris J. Kavvadias, Frosso S. Makri, Michael N. Vrahatis:
Efficiently Computing Many Roots of a Function. SIAM J. Sci. Comput. 27(1): 93-107 (2005) - 2004
- [j22]George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Neural network-based colonoscopic diagnosis using on-line learning and differential evolution. Appl. Soft Comput. 4(4): 369-379 (2004) - [j21]M. G. Karagiannopoulos, Michael N. Vrahatis, Gerasimos C. Meletiou:
A note on a secure voting system on a public network. Networks 43(4): 224-225 (2004) - [j20]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
On the Computation of All Global Minimizers Through Particle Swarm Optimization. IEEE Trans. Evol. Comput. 8(3): 211-224 (2004) - 2003
- [j19]Elena C. Laskari, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Evolutionary Operators in Global Optimization with Dynamic Search Trajectories. Numer. Algorithms 34(2-4): 393-403 (2003) - 2002
- [j18]Michael N. Vrahatis, Basilis Boutsinas, Panagiotis D. Alevizos, Georgios Pavlides:
The New k-Windows Algorithm for Improving the k-Means Clustering Algorithm. J. Complex. 18(1): 375-391 (2002) - [j17]Bernard Mourrain, Michael N. Vrahatis, Jean-Claude Yakoubsohn:
On the Complexity of Isolating Real Roots and Computing with Certainty the Topological Degree. J. Complex. 18(2): 612-640 (2002) - [j16]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Recent approaches to global optimization problems through Particle Swarm Optimization. Nat. Comput. 1(2-3): 235-306 (2002) - [j15]Vassilis P. Plagianakos, Michael N. Vrahatis:
Parallel evolutionary training algorithms for "hardware-friendly" neural networks. Nat. Comput. 1(2-3): 307-322 (2002) - [j14]George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Globally convergent algorithms with local learning rates. IEEE Trans. Neural Networks 13(3): 774-779 (2002) - [j13]Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis:
Deterministic nonmonotone strategies for effective training of multilayer perceptrons. IEEE Trans. Neural Networks 13(6): 1268-1284 (2002) - 2001
- [j12]Basilis Boutsinas, Michael N. Vrahatis:
Artificial nonmonotonic neural networks. Artif. Intell. 132(1): 1-38 (2001) - 2000
- [j11]Michael N. Vrahatis, George D. Magoulas, Vassilis P. Plagianakos:
Globally Convergent Modification of the Quickprop Method. Neural Process. Lett. 12(2): 159-170 (2000) - [j10]George D. Magoulas, Michael N. Vrahatis:
A class of adaptive learning rate algorithms derived by one-dimensional subminimization methods. Neural Parallel Sci. Comput. 8(2): 147-168 (2000) - 1999
- [j9]George D. Magoulas, Michael N. Vrahatis, George S. Androulakis:
Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods. Neural Comput. 11(7): 1769-1796 (1999) - [j8]Dimitris J. Kavvadias, Frosso S. Makri, Michael N. Vrahatis:
Locating and Computing Arbitrarily Distributed Zeros. SIAM J. Sci. Comput. 21(3): 954-969 (1999) - 1997
- [j7]George D. Magoulas, Michael N. Vrahatis, George S. Androulakis:
Effective Backpropagation Training with Variable Stepsize. Neural Networks 10(1): 69-82 (1997) - 1996
- [j6]Michael N. Vrahatis, Evangelia Triantafyllou:
Locating, characterizing and computing the stationary points of a function. Reliab. Comput. 2(2): 187-193 (1996) - [j5]Dimitris J. Kavvadias, Michael N. Vrahatis:
Locating and Computing All the Simple Roots and Extrema of a Function. SIAM J. Sci. Comput. 17(5): 1232-1248 (1996) - 1995
- [j4]Theodoula N. Grapsa, Michael N. Vrahatis:
A new dimension - reducing method for solving systems of nonlinear equations. Int. J. Comput. Math. 55(3-4): 235-244 (1995) - 1990
- [j3]T. N. Grapsa, Michael N. Vrahatis, Tassos Bountis:
Solving systems of nonlinear equations In using a rotating hyperplane in. Int. J. Comput. Math. 35(1-4): 133-151 (1990) - 1988
- [j2]Michael N. Vrahatis:
Solving systems of nonlinear equations using the nonzero value of the topological degree. ACM Trans. Math. Softw. 14(4): 312-329 (1988) - [j1]Michael N. Vrahatis:
Algorithm 666: Chabis: a mathematical software package for locating and evaluating roots of systems of nonlinear equations. ACM Trans. Math. Softw. 14(4): 330-336 (1988)
Conference and Workshop Papers
- 2023
- [c90]Konstantinos I. Chatzilygeroudis, Constantinos G. Tsakonas, Michael N. Vrahatis:
Evolving Dynamic Locomotion Policies in Minutes. IISA 2023: 1-8 - [c89]Konstantinos I. Chatzilygeroudis, Michael N. Vrahatis:
Fast and Robust Constrained Optimization via Evolutionary and Quadratic Programming. LION 2023: 46-61 - 2022
- [c88]Michael N. Vrahatis:
Survey on Generalizations of the Intermediate Value Theorem and Applications. CASC 2022: 1-17 - [c87]Panos K. Syriopoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Survey on KNN Methods in Data Science. LION 2022: 379-393 - [c86]Panos K. Syriopoulos, Nektarios G. Kalampalikis, Michael N. Vrahatis:
Maximizing the Eigenvalue-Gap and Promoting Sparsity of Doubly Stochastic Matrices with PSO. LION 2022: 535-548 - 2021
- [c85]Emmanouil K. Ikonomakis, Marilena M. Bourdakou, George Kolios, Michael N. Vrahatis, George M. Spyrou:
Computational insights on the molecular mechanisms across breast cancer progression combining gene differential expression and co-expression. BHI 2021: 1-5 - [c84]Konstantinos I. Chatzilygeroudis, Aristidis G. Vrahatis, Sotiris K. Tasoulis, Michael N. Vrahatis:
Feature Selection in Single-Cell RNA-seq Data via a Genetic Algorithm. LION 2021: 66-79 - 2019
- [c83]Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis:
A Deep Dense Neural Network for Bankruptcy Prediction. EANN 2019: 435-444 - [c82]Stamatios-Aggelos N. Alexandropoulos, Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Stacking Strong Ensembles of Classifiers. AIAI 2019: 545-556 - [c81]Georgios S. Temponeras, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Financial Fraudulent Statements Detection through a Deep Dense Artificial Neural Network. IISA 2019: 1-5 - [c80]Michael N. Vrahatis:
Generalizations of the Intermediate Value Theorem for Approximating Fixed Points and Zeros of Continuous Functions. NUMTA (2) 2019: 223-238 - 2017
- [c79]Christos K. Aridas, Stamatios-Aggelos N. Alexandropoulos, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems. EANN 2017: 111-121 - [c78]Stavros P. Adam, Aristidis C. Likas, Michael N. Vrahatis:
Interval Analysis Based Neural Network Inversion: A Means for Evaluating Generalization. EANN 2017: 314-326 - 2016
- [c77]Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Increasing Diversity in Random Forests Using Naive Bayes. AIAI 2016: 75-86 - [c76]Christos K. Aridas, Sotiris B. Kotsiantis, Michael N. Vrahatis:
Combining Prototype Selection with Local Boosting. AIAI 2016: 94-105 - 2015
- [c75]Anastasia-Dimitra Lipitakis, Gerasimos S. Antzoulatos, Sotiris Kotsiantis, Michael N. Vrahatis:
Integrating global and local boosting. IISA 2015: 1-6 - [c74]Stavros P. Adam, Dimitris A. Karras, George D. Magoulas, Michael N. Vrahatis:
Reliable estimation of a neural network's domain of validity through interval analysis based inversion. IJCNN 2015: 1-8 - 2013
- [c73]Emmanouil K. Ikonomakis, George M. Spyrou, Panos A. Ligomenides, Michael N. Vrahatis:
Performance evaluation of clustering algorithms on microcalcifications as mammography findings. BIBE 2013: 1-4 - [c72]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Michael N. Vrahatis:
evoDrummer: Deriving Rhythmic Patterns through Interactive Genetic Algorithms. EvoMUSART 2013: 25-36 - 2012
- [c71]Ilias S. Kotsireas, Konstantinos E. Parsopoulos, Grigoris S. Piperagkas, Michael N. Vrahatis:
Ant-Based Approaches for Solving Autocorrelation Problems. ANTS 2012: 220-227 - [c70]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Michael N. Vrahatis, Nikolaos Kanellopoulos:
Real-time drums transcription with characteristic bandpass filtering. Audio Mostly Conference 2012: 152-159 - [c69]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Multimodal optimization using niching differential evolution with index-based neighborhoods. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c68]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c67]Stavros P. Adam, George D. Magoulas, Michael N. Vrahatis:
Direct Zero-Norm Minimization for Neural Network Pruning and Training. EANN 2012: 295-304 - [c66]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Andreas Floros, Michael N. Vrahatis:
Interactive Evolution of 8-Bit Melodies with Genetic Programming towards Finding Aesthetic Measures for Sound. EvoMUSART 2012: 141-152 - [c65]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Nikolaos Kanellopoulos, Michael N. Vrahatis:
Genetic evolution of L and FL-systems for the production of rhythmic sequences. GECCO (Companion) 2012: 461-468 - [c64]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Michael N. Vrahatis:
Intelligent Real-Time Music Accompaniment for Constraint-Free Improvisation. ICTAI 2012: 444-451 - [c63]Maximos A. Kaliakatsos-Papakostas, Andreas Floros, Michael N. Vrahatis:
Intelligent Generation of Rhythmic Sequences Using Finite L-systems. IIH-MSP 2012: 424-427 - [c62]Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Tracking Differential Evolution Algorithms: An Adaptive Approach through Multinomial Distribution Tracking with Exponential Forgetting. SETN 2012: 214-222 - 2011
- [c61]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Michael N. Vrahatis:
Weighted Markov Chain Model for Musical Composer Identification. EvoApplications (2) 2011: 334-343 - [c60]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Michael N. Vrahatis:
Feature Extraction Using Pitch Class Profile Information Entropy. MCM 2011: 354-357 - [c59]Gerasimos Antzoulatos, Michael N. Vrahatis:
α-Clusterable Sets. ECML/PKDD (1) 2011: 108-123 - [c58]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Finding multiple global optima exploiting differential evolution's niching capability. SDE 2011: 80-87 - 2010
- [c57]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c56]Maximos A. Kaliakatsos-Papakostas, Michael G. Epitropakis, Michael N. Vrahatis:
Musical Composer Identification through Probabilistic and Feedforward Neural Networks. EvoApplications (2) 2010: 411-420 - 2009
- [c55]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Evolutionary adaptation of the differential evolution control parameters. IEEE Congress on Evolutionary Computation 2009: 1359-1366 - [c54]Stavros P. Adam, Dimitrios A. Karras, Michael N. Vrahatis:
A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World Tasks. ICDM (Posters) 2009: 38-52 - [c53]Vasileios L. Georgiou, Sonia Malefaki, Konstantinos E. Parsopoulos, Philipos D. Alevizos, Michael N. Vrahatis:
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks. LION 2009: 30-44 - 2008
- [c52]Vasileios L. Georgiou, Philipos D. Alevizos, Michael N. Vrahatis:
Fuzzy Evolutionary Probabilistic Neural Networks. ANNPR 2008: 113-124 - [c51]Konstantinos E. Parsopoulos, Voula C. Georgopoulos, Michael N. Vrahatis:
A technique for the visualization of population-based algorithms. IEEE Congress on Evolutionary Computation 2008: 1694-1701 - [c50]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Balancing the exploration and exploitation capabilities of the Differential Evolution Algorithm. IEEE Congress on Evolutionary Computation 2008: 2686-2693 - [c49]Konstantinos E. Parsopoulos, Konstantina Skouri, Michael N. Vrahatis:
Particle Swarm Optimization for Tackling Continuous Review Inventory Models. EvoWorkshops 2008: 103-112 - [c48]A. D. Klamargias, Konstantinos E. Parsopoulos, Philipos D. Alevizos, Michael N. Vrahatis:
Particle filtering with particle swarm optimization in systems with multiplicative noise. GECCO 2008: 57-62 - [c47]Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Non-monotone differential evolution. GECCO 2008: 527-528 - [c46]Stavros P. Adam, Dimitrios A. Karras, Michael N. Vrahatis:
Revisiting the Problem of Weight Initialization for Multi-Layer Perceptrons Trained with Back Propagation. ICONIP (2) 2008: 308-315 - 2007
- [c45]Nicos G. Pavlidis, E. G. Pavlidis, Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Computational intelligence algorithms for risk-adjusted trading strategies. IEEE Congress on Evolutionary Computation 2007: 540-547 - [c44]Yiannis G. Petalas, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Entropy-based Memetic Particle Swarm Optimization for computing periodic orbits of nonlinear mappings. IEEE Congress on Evolutionary Computation 2007: 2040-2047 - [c43]Yiannis G. Petalas, Konstantinos E. Parsopoulos, Elpiniki I. Papageorgiou, Petros P. Groumpos, Michael N. Vrahatis:
Enhanced Learning in Fuzzy Simulation Models Using Memetic Particle Swarm Optimization. SIS 2007: 16-22 - 2006
- [c42]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Studying the Performance of Unified Particle Swarm Optimization on the Single Machine Total Weighted Tardiness Problem. Australian Conference on Artificial Intelligence 2006: 760-769 - [c41]Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis:
Human Designed Vs. Genetically Programmed Differential Evolution Operators. IEEE Congress on Evolutionary Computation 2006: 1880-1886 - [c40]Dimitris K. Tasoulis, Elena C. Laskari, Gerasimos C. Meletiou, Michael N. Vrahatis:
Privacy Preserving Unsupervised Clustering over Vertically Partitioned Data. ICCSA (5) 2006: 635-643 - [c39]Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Differential Evolution Algorithms for Finding Predictive Gene Subsets in Microarray Data. AIAI 2006: 484-491 - 2005
- [c38]Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Clustering in evolutionary algorithms to efficiently compute simultaneously local and global minima. Congress on Evolutionary Computation 2005: 1847-1854 - [c37]Dimitris K. Tasoulis, Michael N. Vrahatis:
The new window density function for efficient evolutionary unsupervised clustering. Congress on Evolutionary Computation 2005: 2388-2394 - [c36]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Unified Particle Swarm Optimization in Dynamic Environments. EvoWorkshops 2005: 590-599 - [c35]Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction. Computational Intelligence 2005: 456-461 - [c34]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems. ICNC (3) 2005: 582-591 - [c33]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Unified particle swarm optimization for tackling operations research problems. SIS 2005: 53-59 - 2004
- [c32]Konstantinos E. Parsopoulos, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Vector evaluated differential evolution for multiobjective optimization. IEEE Congress on Evolutionary Computation 2004: 204-211 - [c31]Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Parallel differential evolution. IEEE Congress on Evolutionary Computation 2004: 2023-2029 - [c30]Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis:
A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm. ESANN 2004: 1-6 - [c29]Konstantinos E. Parsopoulos, Elpiniki Papageorgiou, Peter P. Groumpos, Michael N. Vrahatis:
Evolutionary Computation Techniques for Optimizing Fuzzy Cognitive Maps in Radiation Therapy Systems. GECCO (1) 2004: 402-413 - [c28]Yiannis G. Petalas, Dimitris K. Tasoulis, Michael N. Vrahatis:
Dynamic Search Trajectory Methods for Neural Network Training. ICAISC 2004: 241-246 - [c27]Elpiniki Papageorgiou, Konstantinos E. Parsopoulos, Peter P. Groumpos, Michael N. Vrahatis:
Fuzzy Cognitive Maps Learning through Swarm Intelligence. ICAISC 2004: 344-349 - [c26]Dimitris K. Tasoulis, Liviu Vladutu, Vassilis P. Plagianakos, Anastasios Bezerianos, Michael N. Vrahatis:
Online Neural Network Training for Automatic Ischemia Episode Detection. ICAISC 2004: 1062-1068 - [c25]Todor Ganchev, Nikos Fakotakis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Generalized locally recurrent probabilistic neural networks for text-independent speaker verification. ICASSP (1) 2004: 41-44 - [c24]Dimitris K. Tasoulis, Michael N. Vrahatis:
Unsupervised distributed clustering. Parallel and Distributed Computing and Networks 2004: 347-351 - 2003
- [c23]Konstantinos E. Parsopoulos, Elpiniki I. Papageorgiou, Peter P. Groumpos, Michael N. Vrahatis:
A first study of fuzzy cognitive maps learning using particle swarm optimization. IEEE Congress on Evolutionary Computation 2003: 1440-1447 - [c22]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Investigating the existence of function roots using particle swarm optimization. IEEE Congress on Evolutionary Computation 2003: 1448-1455 - [c21]Thomas Bartz-Beielstein, Philipp Limbourg, Jörn Mehnen, Karlheinz Schmitt, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Particle swarm optimizers for Pareto optimization with enhanced archiving techniques. IEEE Congress on Evolutionary Computation 2003: 1780-1787 - [c20]Nicos G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis:
Financial forecasting through unsupervised clustering and evolutionary trained neural networks. IEEE Congress on Evolutionary Computation 2003: 2314-2321 - [c19]Todor Ganchev, Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis:
Locally recurrent probabilistic neural network for text-independent speaker verification. INTERSPEECH 2003: 1673-1676 - [c18]Dimitris K. Tasoulis, Panagiota Spyridonos, Nicos G. Pavlidis, Dionisis A. Cavouras, Panagiota Ravazoula, George Nikiforidis, Michael N. Vrahatis:
Urinary Bladder Tumor Grade Diagnosis Using On-line Trained Neural Networks. KES 2003: 199-206 - [c17]Dimitris K. Tasoulis, Panagiotis D. Alevizos, Basilis Boutsinas, Michael N. Vrahatis:
Parallel Unsupervised k-Windows: An Efficient Parallel Clustering Algorithm. PaCT 2003: 336-344 - [c16]Panagiotis D. Alevizos, Dimitris K. Tasoulis, Michael N. Vrahatis:
Parallelizing the Unsupervised k-Windows Clustering Algorithm. PPAM 2003: 225-232 - [c15]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Computing periodic orbits of nondifferentiable/discontinuous mappings through particle swarm optimization. SIS 2003: 34-41 - 2002
- [c14]Elena C. Laskari, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Particle swarm optimization for minimax problems. IEEE Congress on Evolutionary Computation 2002: 1576-1581 - [c13]Elena C. Laskari, Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Particle swarm optimization for integer programming. IEEE Congress on Evolutionary Computation 2002: 1582-1587 - [c12]Adam V. Adamopoulos, Basilis Boutsinas, Michael N. Vrahatis, Photios A. Anninos:
Analysis of epileptic magnetoencephalogram dynamics through clustering algorithms. DSP 2002: 607-610 - [c11]Panagiotis D. Alevizos, Basilis Boutsinas, Dimitris K. Tasoulis, Michael N. Vrahatis:
Improving the Orthogonal Range Search k -Windows Algorithm. ICTAI 2002: 239-245 - [c10]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Particle swarm optimization method in multiobjective problems. SAC 2002: 603-607 - 2000
- [c9]George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Development and Convergence Analysis of Training Algorithms with Local Learning Rate Adaptation. IJCNN (1) 2000: 21-26 - [c8]Vassilis P. Plagianakos, Michael N. Vrahatis:
Training Neural Networks with Threshold Activation Functions and Constrained Integer Weights. IJCNN (5) 2000: 161-166 - 1999
- [c7]Vassilis P. Plagianakos, Michael N. Vrahatis:
Neural network training with constrained integer weights. CEC 1999: 2007-2013 - [c6]Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis:
Nonmonotone learning rules for backpropagation networks. ICECS 1999: 291-294 - [c5]George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Effective neural network training with a different learning rate for each weight. ICECS 1999: 591-594 - [c4]Michael N. Vrahatis, George D. Magoulas, Vassilis P. Plagianakos:
Convergence analysis of the Quickprop method. IJCNN 1999: 1209-1214 - [c3]Vassilis P. Palgianakos, Michael N. Vrahatis, George D. Magoulas:
Nonmonotone methods for backpropagation training with adaptive learning rate. IJCNN 1999: 1762-1767 - [c2]George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Sign-methods for training with imprecise error function and gradient values. IJCNN 1999: 1768-1773 - 1996
- [c1]George D. Magoulas, Michael N. Vrahatis, George S. Androulakis:
A new method in neural network supervised training with imprecision. ICECS 1996: 287-290
Parts in Books or Collections
- 2021
- [p4]Konstantinos E. Parsopoulos, Michael N. Vrahatis:
Deflection and Stretching Techniques for Detection of Multiple Minimizers in Multimodal Optimization Problems. Metaheuristics for Finding Multiple Solutions 2021: 129-144 - 2008
- [p3]Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis:
Computational Intelligence Algorithms and DNA Microarrays. Computational Intelligence in Bioinformatics 2008: 1-31 - 2007
- [p2]Elena C. Laskari, Gerasimos C. Meletiou, Yannis C. Stamatiou, Michael N. Vrahatis:
Cryptography and Cryptanalysis Through Computational Intelligence. Computational Intelligence in Information Assurance and Security 2007: 1-49 - 2006
- [p1]Dimitris K. Tasoulis, Dimitrios Zeimpekis, Efstratios Gallopoulos, Michael N. Vrahatis:
Oriented k-windows: A PCA driven clustering method. Advances in Web Intelligence and Data Mining 2006: 319-328
Informal and Other Publications
- 2024
- [i5]Michael N. Vrahatis:
Generalization of the Apollonius theorem for simplices and related problems. CoRR abs/2401.03232 (2024) - [i4]Michael N. Vrahatis:
Towards the mathematical foundation of the minimum enclosing ball and related problems. CoRR abs/2402.06629 (2024) - 2022
- [i3]Ilias S. Kotsireas, Panos M. Pardalos, Alexander Semenov, William T. Trevena, Michael N. Vrahatis:
Survey of Methods for Solving Systems of Nonlinear Equations, Part I: Root-finding Approaches. CoRR abs/2208.08530 (2022) - [i2]Ilias S. Kotsireas, Panos M. Pardalos, Alexander Semenov, William T. Trevena, Michael N. Vrahatis:
Survey of Methods for Solving Systems of Nonlinear Equations, Part II: Optimization Based Approaches. CoRR abs/2208.08532 (2022) - 2005
- [i1]Charalampos Skokos, Konstantinos E. Parsopoulos, Panos A. Patsis, Michael N. Vrahatis:
Particle Swarm Optimization: An efficient method for tracing periodic orbits in 3D galactic potentials. CoRR abs/astro-ph/0502164 (2005)
Coauthor Index
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