The Kanerva Machine: A Generative Distributed Memory

International Conference on Learning Representations, Volume abs/1804.01756, 2018.

Cited by: 13|Bibtex|Views201
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

We present an end-to-end trained memory system that quickly adapts to new data and generates samples like them. Inspired by Kanerva’s sparse distributed memory, it has a robust distributed reading and writing mechanism. The memory is analytically tractable, which enables optimal on-line compression via a Bayesian update-rule. We formulate...More

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