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Solving the linear interval tolerance problem for weight initialization of neural networks.

, , , and . Neural Networks, (2014)

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A Data Mining Approach in the Analysis of the Weight Space of Multilayer Perceptron Solving Complex Real World Tasks., , and . ICDM (Posters), page 38-52. ibai Publishing, (2009)Solving the linear interval tolerance problem for weight initialization of neural networks., , , and . Neural Networks, (2014)Reliable estimation of a neural network's domain of validity through interval analysis based inversion., , , and . IJCNN, page 1-8. IEEE, (2015)Direct Zero-Norm Minimization for Neural Network Pruning and Training., , and . EANN, volume 311 of Communications in Computer and Information Science, page 295-304. Springer, (2012)Evaluating generalization through interval-based neural network inversion., , and . Neural Comput. Appl., 31 (12): 9241-9260 (2019)Intelligent Techniques and Hybrid Systems Experiments Using the Acumen Modeling and Simulation Environment., , and . AIAI, volume 627 of IFIP Advances in Information and Communication Technology, page 531-542. Springer, (2021)Ανάπτυξη και θεμελίωση μεθόδων για αξιόπιστους νευρωνικούς υπολογισμούς. University of Patras, Greece, (2016)National Archive of PhD Theses: oai:10442/38490.Revisiting the Problem of Weight Initialization for Multi-Layer Perceptrons Trained with Back Propagation., , and . ICONIP (2), volume 5507 of Lecture Notes in Computer Science, page 308-315. Springer, (2008)Interval Analysis Based Neural Network Inversion: A Means for Evaluating Generalization., , and . EANN, volume 744 of Communications in Computer and Information Science, page 314-326. Springer, (2017)