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...
| প্রধান লেখক: | , , |
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| বিন্যাস: | প্রবন্ধ |
| ভাষা: | English |
| প্রকাশিত: |
IEEE
2023-01-01
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| মালা: | IEEE Access |
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | https://ieeexplore.ieee.org/document/10053845/ |