Why Hyperdimensional Computing (HDC)? Unlike traditional dense ML embeddings (e.g., Word2Vec or BERT) which are learned iteratively via backpropagation and reside as opaque points in a continuous ...

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Abstract: Most of the existing hypernetwork representation learning methods fail to fully consider the hyperedges, leading to the untapped potential of information contained within the hyperedges. To ...

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Abstract: The transformer model examines embedding approaches sensitive to context variation in natural language processing. Sense-enhanced embeddings, where words are represented as vectors, involve ...