Learning Sparse, Distributed Representations using the Hebbian Principle

14 Nov 2016 Aseem Wadhwa Upamanyu Madhow

The "fire together, wire together" Hebbian model is a central principle for learning in neuroscience, but surprisingly, it has found limited applicability in modern machine learning. In this paper, we take a first step towards bridging this gap, by developing flavors of competitive Hebbian learning which produce sparse, distributed neural codes using online adaptation with minimal tuning... (read more)

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