Why AI Works
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-68624-6_4
Reference17 articles.
1. Antonio Auffinger, Gérard Ben Arous, and Jiří Černý “Random Matrices and Complexity of Spin Glasses”. In: Communications on Pure and Applied Mathematics 66.2 (2013), pp. 165–201. doi: https://doi.org/10.1002/cpa.21422.
2. A. Choromanska et al. “The Loss Surfaces of Multilayer Networks”. In: Journal of Machine Learning Research 38.8 (2015), pp. 192–204.
3. Y. Dauphin et al. “Identifying and Attacking the Saddle Point Problem in High-Dimensional Non-convex Optimization”. In: Proceedings of Neural Information Processing Systems. 2014.
4. David S. Dean and Satya N. Majumdar. “Large Deviations of Extreme Eigenvalues of Random Matrices”. In: Phys. Rev. Lett. 97 16 (2006), pp. 160–201. doi: https://doi.org/10.1103/PhysRevLett.97.160201.
5. Jean-Pierre Dedieu and Gregorio Malajovich. “On the Number of Minima of a Random Polynomial”. In: Journal of Complexity 24.2 (2008), pp. 89–108. issn: 0885-064X. doi: https://doi.org/10.1016/j.jco.2007.09.003.
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