On the Practical Robustness of the Nesterov’s Accelerated Quasi-Newton Method
Keywords:Optimization Algorithm, Quasi-Newton Method, Neural Networks, Second-order, Nesterov’s Accelerated Gradient
AbstractThis study focuses on the Nesterov's accelerated quasi-Newton (NAQ) method in the context of deep neural networks (DNN) and its applications. The thesis objective is to confirm the robustness and efficiency of Nesterov's acceleration to quasi-Netwon (QN) methods by developing practical algorithms for different fields of optimization problems.
How to Cite
Indrapriyadarsini, S., Ninomiya, H., Kamio, T., & Asai, H. (2022). On the Practical Robustness of the Nesterov’s Accelerated Quasi-Newton Method. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12884-12885. https://doi.org/10.1609/aaai.v36i11.21579
The Twenty - Seventh AAAI / SIGAI Doctoral Consortium