1. J. Carner, A. Mestres, E. Alarcón, A. Cabellos, “Machine learning-based network modeling: An artificial neural network model vs a theoretical inspired model,” 2017 Ninth International Conference on Ubiquitou H. Zhang, L. Zhang and Y. Jiang, “Overfitting and Underfitting Analysis for Deep Learning Based End-to-end Communication Systems,” 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), Xi'an, China, 2019, pp. 1-6.
2. Vishal Dineshkumar Soni 2019. IOT connected with e-learning. Int. J. Integr. Educ.. 2, 5 (Oct. 2019), 273-277. DOI:https://doi.org/10.31149/ijie.v2i5.496.
3. D. Dai, M. Hahner, L. V. Gool, “Texture Underfitting for Domain Adaptation,” 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 2019, pp. 547-552.
4. I. Bilbao, J. Bilbao, “Overfitting problem and the over-training in the era of data: Particularly for Artificial Neural Networks,” 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS), Cairo, 2017, pp. 173-177.
5. Soni, Vishal Dineshkumar, Challenges and Solution for Artificial Intelligence in Cybersecurity of the USA (June 10, 2020). Available at SSRN: https://ssrn.com/abstract=3624487 or http://dx.doi.org/10.2139/ssrn.3624487.