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Stavros P. Adam
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2020 – today
- 2022
- [i1]Stavros P. Adam, Aristidis C. Likas:
A Set Membership Approach to Discovering Feature Relevance and Explaining Neural Classifier Decisions. CoRR abs/2204.02241 (2022) - 2021
- [c6]Sotirios Tzamaras, Stavros P. Adam, Walid Taha:
Intelligent Techniques and Hybrid Systems Experiments Using the Acumen Modeling and Simulation Environment. AIAI 2021: 531-542
2010 – 2019
- 2019
- [j3]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) - 2017
- [c5]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
- [b1]Stavros P. Adam:
Ανάπτυξη και θεμελίωση μεθόδων για αξιόπιστους νευρωνικούς υπολογισμούς. University of Patras, Greece, 2016 - [j2]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
- [c4]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
- [j1]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
- [c3]Stavros P. Adam, George D. Magoulas, Michael N. Vrahatis:
Direct Zero-Norm Minimization for Neural Network Pruning and Training. EANN 2012: 295-304
2000 – 2009
- 2009
- [c2]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 - 2008
- [c1]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
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