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Alleviating catastrophic forgetting via multi-objective learning

Jin, Y, Sendhoff, B, Jin, Y and Sendhoff, B (2006) Alleviating catastrophic forgetting via multi-objective learning

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Abstract

Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general point of view, catastrophic forgetting reflects the stability-plasticity dilemma, which is one of the several dilemmas to be addressed in learning systems: to retain the stored memory while learning new information. Different to the existing approaches, we introduce a Pareto-optimality based multi-objective learning framework for alleviating catastrophic learning. Compared to the single-objective learning methods, multi-objective evolutionary learning with the help of pseudorehearsal is shown to be more promising in dealing with the stability-plasticity dilemma. © 2006 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
AuthorsEmailORCID
Jin, YUNSPECIFIEDUNSPECIFIED
Sendhoff, BUNSPECIFIEDUNSPECIFIED
Jin, YUNSPECIFIEDUNSPECIFIED
Sendhoff, BUNSPECIFIEDUNSPECIFIED
Date : 2006
Identification Number : https://doi.org/10.1109/IJCNN.2006.247332
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:42
Last Modified : 28 Mar 2017 14:42
URI: http://epubs.surrey.ac.uk/id/eprint/532835

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