A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks

A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks

Over the years, researchers have proposed multiple approaches to reduce the number of parameters Deep Learning models have. Due to the complexity of compressing models, some authors have opted to train Reinforcement Learning agents that learn how to compress a particular model without losing conside...

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Bibliographic Details
Main Authors: Gabriel Gonzalez-Sahagun, Santiago Enrique Conant-Pablos, Jose Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Computer vision
deep learning
model compression
model optimization
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10494337/

Internet

https://ieeexplore.ieee.org/document/10494337/

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