Mixed‐Precision Continual Learning Based on Computational Resistance Random Access Memory

Mixed‐Precision Continual Learning Based on Computational Resistance Random Access Memory

Artificial neural networks have acquired remarkable achievements in the field of artificial intelligence. However, it suffers from catastrophic forgetting when dealing with continual learning problems, i.e., the loss of previously learned knowledge upon learning new information. Although several con...

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Bibliographic Details
Main Authors: Yi Li, Woyu Zhang, Xiaoxin Xu, Yifan He, Danian Dong, Nanjia Jiang, Fei Wang, Zeyu Guo, Shaocong Wang, Chunmeng Dou, Yongpan Liu, Zhongrui Wang, Dashan Shang
Format: Article
Language:English
Published: Wiley 2022-08-01
Series:Advanced Intelligent Systems
Subjects:
continual learning
in-memory computing
mixed precision
resistance random access memory
Online Access:https://doi.org/10.1002/aisy.202200026

Internet

https://doi.org/10.1002/aisy.202200026

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