AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Hyperdimensional computing (HDC) is attractive for efficient and robust learning, but conventional inference still encodes every query independently, repeatedly paying the cost of high-dimensional projection. We introduce SupHDC, a new inference paradigm that processes multiple queries through a shared encoding computa...
The Superposed Latent Autoencoder (SLAE) is introduced, which preserves high-capacity latent representations while sharing storage through learned superposition, and suggests a new principle for representation compression: instead of making every latent smaller, keep representations wide and let them share memory.
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