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cs.LG2025
Low-Complexity Inference in Continual Learning via Compressed Knowledge Transfer
Zhenrong Liu, Janne M. J. Huttunen, Mikko Honkala
Continual learning (CL) aims to train models that can learn a sequence of tasks without forgetting previously acquired knowledge. A core challenge in CL is balancing stability -- p…
cs.LG2023
Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning
Zhenrong Liu, Yang Li, Yi Gong +1
In continual learning, networks confront a trade-off between stability and plasticity when trained on a sequence of tasks. To bolster plasticity without sacrificing stability, we p…