A theoretical framework for end-to-end learning of deep neural networks with applications to robotics

Deep Learning (DL) systems are difficult to analyze and proving convergence of DL algorithms like backpropagation is an extremely challenging task as it is a highly non-convex and high-dimensional problem. When using DL algorithms in robotic systems, theoretical analysis of stability, convergence, a...

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Bibliographic Details
Main Authors: Li, Sitan, Nguyen, Huu-Thiet, Cheah, Chien Chern
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/168831
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Institution: Nanyang Technological University
Language: English
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