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cs.IT2026
Derandomizing Dense Binary Hypervector Codebooks for Quantized Scalars
Dmitri Rachkovskij, Evgeny Osipov, Olexander Volkov +2
Hyperdimensional computing and vector symbolic architectures often represent quantized scalar levels by dense binary codebooks whose level-to-level similarity is intended to follow…
cs.LG2026
Systematic Characterization of Minimal Deep Learning Architectures: A Unified Analysis of Convergence, Pruning, and Quantization
Ziwei Zheng, Huizhi Liang, Vaclav Snasel +4
Deep learning networks excel at classification, yet identifying minimal architectures that reliably solve a task remains challenging. We present a computational methodology for sys…