SPeCiaL: Self-Supervised Pretraining for Continual Learning

• URL: http://arxiv.org/abs/2106.09065v1
• Date: Wed, 16 Jun 2021 18:15:15 GMT
• Title: SPeCiaL: Self-Supervised Pretraining for Continual Learning
• Authors: Lucas Caccia, Joelle Pineau
• Abstract summary: SPeCiaL is a method for unsupervised pretraining of representations tailored for continual learning. We evaluate SPeCiaL in the Continual Few-Shot Learning setting, and show that it can match or outperform other supervised pretraining approaches.
• Score: 49.34919926042038
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents SPeCiaL: a method for unsupervised pretraining of representations tailored for continual learning. Our approach devises a meta-learning objective that differentiates through a sequential learning process. Specifically, we train a linear model over the representations to match different augmented views of the same image together, each view presented sequentially. The linear model is then evaluated on both its ability to classify images it just saw, and also on images from previous iterations. This gives rise to representations that favor quick knowledge retention with minimal forgetting. We evaluate SPeCiaL in the Continual Few-Shot Learning setting, and show that it can match or outperform other supervised pretraining approaches.

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