Revisiting the Problem of Weight Initialization for Multi-Layer Perceptrons Trained with Back Propagation. - Stavros P. Adam; Dimitrios A. Karras; Michael N. Vrahatis (ICONIP (2), 2008)

A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World Tasks. - Stavros P. Adam; Dimitrios A. Karras; Michael N. Vrahatis (ICDM (Posters), 2009)

Direct Zero-Norm Minimization for Neural Network Pruning and Training. - Stavros P. Adam; George D. Magoulas; Michael N. Vrahatis (EANN, 2012)

Solving the linear interval tolerance problem for weight initialization of neural networks. - Stavros P. Adam; Dimitrios A. Karras; George D. Magoulas; Michael N. Vrahatis (Neural Networks, 2014)

Reliable estimation of a neural network's domain of validity through interval analysis based inversion. - Stavros P. Adam; Dimitris A. Karras; George D. Magoulas; Michael N. Vrahatis (IJCNN, 2015)

Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach. - Stavros P. Adam; George D. Magoulas; Dimitrios A. Karras; Michael N. Vrahatis (J. Mach. Learn. Res., 2016)

Ανάπτυξη και θεμελίωση μεθόδων για αξιόπιστους νευρωνικούς υπολογισμούς - Stavros P. Adam (2016)

Interval Analysis Based Neural Network Inversion: A Means for Evaluating Generalization. - Stavros P. Adam; Aristidis C. Likas; Michael N. Vrahatis (EANN, 2017)

Evaluating generalization through interval-based neural network inversion. - Stavros P. Adam; Aristidis C. Likas; Michael N. Vrahatis (Neural Comput. Appl., 2019)

Intelligent Techniques and Hybrid Systems Experiments Using the Acumen Modeling and Simulation Environment. - Sotirios Tzamaras; Stavros P. Adam; Walid Taha (AIAI, 2021)

A Set Membership Approach to Discovering Feature Relevance and Explaining Neural Classifier Decisions. - Stavros P. Adam; Aristidis C. Likas (CoRR, 2022)