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Michael N. Vrahatis: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    Studying the Performance of Unified Particle Swarm Optimization on the Single Machine Total Weighted Tardiness Problem. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2006, pp:760-769 [Conf]
  2. Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis
    A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm. [Citation Graph (0, 0)][DBLP]
    ESANN, 2004, pp:1-6 [Conf]
  3. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    Unified Particle Swarm Optimization in Dynamic Environments. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2005, pp:590-599 [Conf]
  4. Konstantinos E. Parsopoulos, Elpiniki Papageorgiou, Peter P. Groumpos, Michael N. Vrahatis
    Evolutionary Computation Techniques for Optimizing Fuzzy Cognitive Maps in Radiation Therapy Systems. [Citation Graph (0, 0)][DBLP]
    GECCO (1), 2004, pp:402-413 [Conf]
  5. N. G. Pavlidis, Dimitris K. Tasoulis, Michael N. Vrahatis
    Time Series Forecasting Methodology for Multiple-Step-Ahead Prediction. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 2005, pp:456-461 [Conf]
  6. Elpiniki Papageorgiou, Konstantinos E. Parsopoulos, Peter P. Groumpos, Michael N. Vrahatis
    Fuzzy Cognitive Maps Learning through Swarm Intelligence. [Citation Graph (0, 0)][DBLP]
    ICAISC, 2004, pp:344-349 [Conf]
  7. Y. G. Petalas, Dimitris K. Tasoulis, Michael N. Vrahatis
    Dynamic Search Trajectory Methods for Neural Network Training. [Citation Graph (0, 0)][DBLP]
    ICAISC, 2004, pp:241-246 [Conf]
  8. Dimitris K. Tasoulis, Liviu Vladutu, Vassilis P. Plagianakos, Anastasios Bezerianos, Michael N. Vrahatis
    Online Neural Network Training for Automatic Ischemia Episode Detection. [Citation Graph (0, 0)][DBLP]
    ICAISC, 2004, pp:1062-1068 [Conf]
  9. Dimitris K. Tasoulis, E. C. Laskari, Gerasimos C. Meletiou, Michael N. Vrahatis
    Privacy Preserving Unsupervised Clustering over Vertically Partitioned Data. [Citation Graph (0, 0)][DBLP]
    ICCSA (5), 2006, pp:635-643 [Conf]
  10. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems. [Citation Graph (0, 0)][DBLP]
    ICNC (3), 2005, pp:582-591 [Conf]
  11. Panagiotis Alevizos, Basilis Boutsinas, Dimitris K. Tasoulis, Michael N. Vrahatis
    Improving the Orthogonal Range Search k -Windows Algorithm. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2002, pp:239-245 [Conf]
  12. Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis
    Differential Evolution Algorithms for Finding Predictive Gene Subsets in Microarray Data. [Citation Graph (0, 0)][DBLP]
    AIAI, 2006, pp:484-491 [Conf]
  13. George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis
    Development and Convergence Analysis of Training Algorithms with Local Learning Rate Adaptation. [Citation Graph (0, 0)][DBLP]
    IJCNN (1), 2000, pp:21-26 [Conf]
  14. Vassilis P. Plagianakos, Michael N. Vrahatis
    Training Neural Networks with Threshold Activation Functions and Constrained Integer Weights. [Citation Graph (0, 0)][DBLP]
    IJCNN (5), 2000, pp:161-166 [Conf]
  15. Dimitris K. Tasoulis, Panagiota Spyridonos, N. G. Pavlidis, Dionisis Cavouras, Panagiota Ravazoula, George Nikiforidis, Michael N. Vrahatis
    Urinary Bladder Tumor Grade Diagnosis Using On-line Trained Neural Networks. [Citation Graph (0, 0)][DBLP]
    KES, 2003, pp:199-206 [Conf]
  16. Dimitris K. Tasoulis, Panagiotis Alevizos, Basilis Boutsinas, Michael N. Vrahatis
    Parallel Unsupervised k-Windows: An Efficient Parallel Clustering Algorithm. [Citation Graph (0, 0)][DBLP]
    PaCT, 2003, pp:336-344 [Conf]
  17. Dimitris K. Tasoulis, Michael N. Vrahatis
    Unsupervised distributed clustering. [Citation Graph (0, 0)][DBLP]
    Parallel and Distributed Computing and Networks, 2004, pp:347-351 [Conf]
  18. Panagiotis Alevizos, Dimitris K. Tasoulis, Michael N. Vrahatis
    Parallelizing the Unsupervised k-Windows Clustering Algorithm. [Citation Graph (0, 0)][DBLP]
    PPAM, 2003, pp:225-232 [Conf]
  19. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    Particle swarm optimization method in multiobjective problems. [Citation Graph (0, 0)][DBLP]
    SAC, 2002, pp:603-607 [Conf]
  20. Basilis Boutsinas, Michael N. Vrahatis
    Artificial nonmonotonic neural networks. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2001, v:132, n:1, pp:1-38 [Journal]
  21. George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis
    Neural network-based colonoscopic diagnosis using on-line learning and differential evolution. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2004, v:4, n:4, pp:369-379 [Journal]
  22. V. L. Georgiou, N. G. Pavlidis, Konstantinos E. Parsopoulos, Ph. D. Alevizos, Michael N. Vrahatis
    New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2006, v:15, n:3, pp:371-396 [Journal]
  23. Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis
    New globally convergent training scheme based on the resilient propagation algorithm. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:64, n:, pp:253-270 [Journal]
  24. Bernard Mourrain, Michael N. Vrahatis, Jean-Claude Yakoubsohn
    On the Complexity of Isolating Real Roots and Computing with Certainty the Topological Degree. [Citation Graph (0, 0)][DBLP]
    J. Complexity, 2002, v:18, n:2, pp:612-640 [Journal]
  25. Michael N. Vrahatis, Basilis Boutsinas, Panagiotis Alevizos, Georgios Pavlides
    The New k-Windows Algorithm for Improving the k-Means Clustering Algorithm. [Citation Graph (0, 0)][DBLP]
    J. Complexity, 2002, v:18, n:1, pp:375-391 [Journal]
  26. Elpiniki Papageorgiou, Konstantinos E. Parsopoulos, Chrysostomos D. Stylios, Petros P. Groumpos, Michael N. Vrahatis
    Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2005, v:25, n:1, pp:95-121 [Journal]
  27. Vassilis P. Plagianakos, Michael N. Vrahatis
    Parallel evolutionary training algorithms for "hardware-friendly" neural networks. [Citation Graph (0, 0)][DBLP]
    Natural Computing, 2002, v:1, n:2-3, pp:307-322 [Journal]
  28. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    Recent approaches to global optimization problems through Particle Swarm Optimization. [Citation Graph (0, 0)][DBLP]
    Natural Computing, 2002, v:1, n:2-3, pp:235-306 [Journal]
  29. Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis
    Evolutionary training of hardware realizable multilayer perceptrons. [Citation Graph (0, 0)][DBLP]
    Neural Computing and Applications, 2006, v:15, n:1, pp:33-40 [Journal]
  30. George D. Magoulas, Michael N. Vrahatis, George S. Androulakis
    Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:7, pp:1769-1796 [Journal]
  31. M. G. Karagiannopoulos, Michael N. Vrahatis, Gerasimos C. Meletiou
    A note on a secure voting system on a public network. [Citation Graph (0, 0)][DBLP]
    Networks, 2004, v:43, n:4, pp:224-225 [Journal]
  32. George D. Magoulas, Michael N. Vrahatis, George S. Androulakis
    Effective Backpropagation Training with Variable Stepsize. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:1, pp:69-82 [Journal]
  33. Michael N. Vrahatis, George D. Magoulas, Vassilis P. Plagianakos
    Globally Convergent Modification of the Quickprop Method. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2000, v:12, n:2, pp:159-170 [Journal]
  34. Aristoklis D. Anastasiadis, George D. Magoulas, Michael N. Vrahatis
    Sign-based learning schemes for pattern classification. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2005, v:26, n:12, pp:1926-1936 [Journal]
  35. Dimitris K. Tasoulis, Michael N. Vrahatis
    Unsupervised clustering on dynamic databases. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2005, v:26, n:13, pp:2116-2127 [Journal]
  36. Konstantinos E. Parsopoulos, Michael N. Vrahatis
    On the Computation of All Global Minimizers Through Particle Swarm Optimization. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2004, v:8, n:3, pp:211-224 [Journal]
  37. N. G. Pavlidis, Michael N. Vrahatis, P. Mossay
    Existence and computation of short-run equilibria in economic geography. [Citation Graph (0, 0)][DBLP]
    Applied Mathematics and Computation, 2007, v:184, n:1, pp:93-103 [Journal]
  38. E. C. Laskari, Gerasimos C. Meletiou, Yannis C. Stamatiou, Michael N. Vrahatis
    Applying evolutionary computation methods for the cryptanalysis of Feistel ciphers. [Citation Graph (0, 0)][DBLP]
    Applied Mathematics and Computation, 2007, v:184, n:1, pp:63-72 [Journal]
  39. Vassilis P. Plagianakos, George D. Magoulas, Michael N. Vrahatis
    Distributed computing methodology for training neural networks in an image-guided diagnostic application. [Citation Graph (0, 0)][DBLP]
    Computer Methods and Programs in Biomedicine, 2006, v:81, n:3, pp:228-235 [Journal]
  40. Dimitris J. Kavvadias, F. S. Makri, Michael N. Vrahatis
    Efficiently Computing Many Roots of a Function. [Citation Graph (0, 0)][DBLP]
    SIAM J. Scientific Computing, 2005, v:27, n:1, pp:93-107 [Journal]
  41. Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis
    Clustering in evolutionary algorithms to efficiently compute simultaneously local and global minima. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:1847-1854 [Conf]
  42. Dimitris K. Tasoulis, Michael N. Vrahatis
    The new window density function for efficient evolutionary unsupervised clustering. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:2388-2394 [Conf]
  43. Ch. Skokos, Konstantinos E. Parsopoulos, P. A. Patsis, Michael N. Vrahatis
    Particle Swarm Optimization: An efficient method for tracing periodic orbits in 3D galactic potentials [Citation Graph (0, 0)][DBLP]
    CoRR, 2005, v:0, n:, pp:- [Journal]
  44. Todor Ganchev, Dimitris K. Tasoulis, Michael N. Vrahatis, Nikos Fakotakis
    Generalized locally recurrent probabilistic neural networks with application to text-independent speaker verification. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2007, v:70, n:7-9, pp:1424-1438 [Journal]

  45. Particle Swarm Optimization for Tackling Continuous Review Inventory Models. [Citation Graph (, )][DBLP]


  46. Musical Composer Identification through Probabilistic and Feedforward Neural Networks. [Citation Graph (, )][DBLP]


  47. Non-monotone differential evolution. [Citation Graph (, )][DBLP]


  48. Particle filtering with particle swarm optimization in systems with multiplicative noise. [Citation Graph (, )][DBLP]


  49. Revisiting the Problem of Weight Initialization for Multi-Layer Perceptrons Trained with Back Propagation. [Citation Graph (, )][DBLP]


  50. A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World Tasks. [Citation Graph (, )][DBLP]


  51. Fuzzy Evolutionary Probabilistic Neural Networks. [Citation Graph (, )][DBLP]


  52. Entropy-based Memetic Particle Swarm Optimization for computing periodic orbits of nonlinear mappings. [Citation Graph (, )][DBLP]


  53. Computational intelligence algorithms for risk-adjusted trading strategies. [Citation Graph (, )][DBLP]


  54. Balancing the exploration and exploitation capabilities of the Differential Evolution Algorithm. [Citation Graph (, )][DBLP]


  55. A technique for the visualization of population-based algorithms. [Citation Graph (, )][DBLP]


  56. Evolutionary adaptation of the differential evolution control parameters. [Citation Graph (, )][DBLP]


  57. Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks. [Citation Graph (, )][DBLP]


  58. Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence. [Citation Graph (, )][DBLP]


  59. Hardware-friendly Higher-Order Neural Network Training using Distributed Evolutionary Algorithms. [Citation Graph (, )][DBLP]


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