DeepQGHO: Quantized Greedy Hyperparameter Optimization in Deep Neural Networks for on-the-Fly Learning

DeepQGHO: Quantized Greedy Hyperparameter Optimization in Deep Neural Networks for on-the-Fly Learning

On-the-fly learning is unavoidable for applications that demand instantaneous deep neural network (DNN) training or where transferring data to the central system for training is costly. Hyperparameter optimization plays a significant role in the performance and reliability in deep learning. Many hyp...

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Bibliographic Details
Main Authors: Anjir Ahmed Chowdhury, Md Abir Hossen, Md Ali Azam, Md Hafizur Rahman
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Greedy algorithm
deep learning
neural networks
online learning
hyperparameter optimization
TinyML
Online Access:https://ieeexplore.ieee.org/document/9676610/

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