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About Application of Meta-Heuristic Algorithms For Training Neural Networks and Deep Learning Architectures
This document provides a comprehensive review of using meta-heuristic algorithms to optimize the training of artificial neural networks and deep learning architectures. It discusses how meta-heuristics can help address limitations of traditional gradient-based backpropagation training methods, such as getting stuck in local minimums. The paper reviews recent applications of meta-heuristics in deep learning and neural networks, classifies different meta-heuristic algorithms, and identifies opportunities to better integrate meta-heuristics and deep learning going forward, such as developing more hybrid meta-heuristic algorithms.
Detailed Information
| Author: | ['Tuấn Trần'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 104 |
| Language: | English |
| Format: | |
| Price: | FREE |
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