all AI news
How To Train a Neural Network with Less GPU Memory: Reversible Residual Networks Review
March 25, 2024, 9:08 a.m. | /u/Human_Statistician48
machinelearningnews www.reddit.com
You will find how reversible residual networks save GPU memory during neural network training. This technique, detailed in "The Reversible Residual Network: Backpropagation Without Storing Activations," allows for efficient training of larger models by not storing activations for backpropagation. Discover its application in reducing hardware requirements while maintaining accuracy in tasks like CIFAR and …
accuracy application backpropagation classification gpu hardware imagenet larger models machinelearningnews memory network networks network training neural network requirements residual save tasks training will
More from www.reddit.com / machinelearningnews
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Senior ML Engineer
@ Carousell Group | Ho Chi Minh City, Vietnam
Data and Insight Analyst
@ Cotiviti | Remote, United States