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ORCIDMichael N. Vrahatis
- > Home > Persons > Michael N. Vrahatis
Publications
- 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
- [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 - 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) - 2012
- [c67]Stavros P. Adam, George D. Magoulas, Michael N. Vrahatis:
Direct Zero-Norm Minimization for Neural Network Pruning and Training. EANN 2012: 295-304 - 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) - [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) - [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) - 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) - [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) - 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) - [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 - 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) - 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) - [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 - 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) - [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 - 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
- [c1]George D. Magoulas, Michael N. Vrahatis, George S. Androulakis:
A new method in neural network supervised training with imprecision. ICECS 1996: 287-290
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