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Classroom Contents
MetaLDC: Meta Learning of Low-Dimensional Computing Classifiers for Fast On-Device Adaptation
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- 1 Intro
- 2 Background: Vector symbolic architecture (VSA)
- 3 Background: Hyper-dimensional computing (HDC/VSA)
- 4 Background: Low-dimensional classifier (LDC)
- 5 MetaLDC framework
- 6 Experimental Setup
- 7 Key results: Accuracy
- 8 Key results: Inference cost
- 9 Key results: Robustness against hardware bit errors
- 10 Additional analysis: Efficacy of the learned representation
- 11 Summary & Takeaways
