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Query-Dependent Reading for Quantized Inner-Product Estimation: A Minimax Separation

Balasubramanian, Krishnakumar et al.
arXiv (All) · Papers
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data-structures-and-algorithmsinformation-theorymachine-learning
We study quantization for inner-product estimation when storage and reading have separate budgets. In the static bit-probe model [Yao, 1981], an encoder stores $w$ bits about $x$ before seeing a query $y$, and a reader probes at most $r<w$ bits to estimate $x^\top y$. Both vectors lie in the $d$-dim
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