ContinualAI Reading Group: "Energy-Based Models for Continual Learning"
Vincenzo Lomonaco
This Friday 18-12-2020 at 17.30 CET, for the ContinualAI Reading Group, Shuang Li (MIT) will present the paper:
Title: "Energy-Based Models for Continual Learning"
Abstract: We motivate Energy-Based Models (EBMs) as a promising model class for continual learning problems. Instead of tackling continual learning via the use of external memory, growing models, or regularization, EBMs have a natural way to support a dynamically-growing number of tasks or classes that causes less interference with previously learned information. We find that EBMs outperform the baseline methods by a large margin on several continual learning benchmarks. We also show that EBMs are adaptable to a more general continual learning setting where the data distribution changes without the notion of explicitly delineated tasks. These observations point towards EBMs as a class of models naturally inclined towards the continual learning regime.
The event will be moderated by: Vincenzo Lomonaco.
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Best regards,
ContinualAI President
Vincenzo Lomonaco