2022
AAAI
AAAI 2022
On the Practical Robustness of the Nesterov’s Accelerated Quasi-Newton Method
Abstract
Abstract This 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.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Mathematics & Optimization
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Keyword Pioneer
— nesterstein acceleration
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio