Adaptive Variational Continual Learning via Task-Heuristic Modelling

• URL: http://arxiv.org/abs/2408.16517v1
• Date: Thu, 29 Aug 2024 13:28:11 GMT
• Title: Adaptive Variational Continual Learning via Task-Heuristic Modelling
• Authors: Fan Yang,
• Abstract summary: Variational continual learning () is a turn-key learning algorithm that has state-of-the-art performance among the best continual learning models. In our work, we explore an extension of the generalized variational continual learning (G) model, named Auto, which combines tasks for informed learning and model optimization.
• Score: 3.6119958671506707
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Variational continual learning (VCL) is a turn-key learning algorithm that has state-of-the-art performance among the best continual learning models. In our work, we explore an extension of the generalized variational continual learning (GVCL) model, named AutoVCL, which combines task heuristics for informed learning and model optimization. We demonstrate that our model outperforms the standard GVCL with fixed hyperparameters, benefiting from the automatic adjustment of the hyperparameter based on the difficulty and similarity of the incoming task compared to the previous tasks.

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