A Note on Scaling in Randomly Rotated Quantization and Its Connection to the CDEF +1 Pythagorean Relation
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Abstract (arXiv)
Quantization schemes based on randomized rotations have recently received renewed attention, including the roles of MMSE and unbiased reconstruction scalings. In this note, we point out the connection to classical results in statistical signal processing and communication theory. Specifically, the two reconstruction scales used in the EDEN line of work admit a natural interpretation as finite-dimensional, realization-dependent counterparts of the Wiener and unbiased coefficients in the classical CDEF formulation. At finite blocklength, the CDEF +1 relation holds pointwise for each rotation realization as an exact geometric (Pythagorean) identity, but does not hold after averaging the distortions over the rotation. The classical SNR relation sfSNRrm MMSE=sfSNRrm MMSE,U+1 is recovered as d→∞: once the overall scale is handled separately, the empirical coordinate statistics of a randomly rotated vector approach their i.i.d. Gaussian counterparts, and the rotation-dependent quantities concentrate. Importantly, EDEN goes beyond this classical correspondence: for every finite d, its Haar-rotation formulation guarantees exact conditional unbiasedness, a stronger property than the second-order notion of unbiasedness in CDEF. We further comment on two distinct roles random rotations play in quantization: one is approximate Gaussianization of the coordinates; the other is decorrelation of reconstruction errors across quantization branches.
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References · 7
- 2024QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMscited by 634
- 2023QuIP: 2-Bit Quantization of Large Language Models With Guaranteescited by 414
- 2016Distributed Mean Estimation with Limited Communicationcited by 136
- 2025TurboQuant: Online Vector Quantization with Near-optimal Distortion Ratecited by 125
- 2021EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learningcited by 55
- 2026A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Workcited by 8
- 2026High-Rate Quantized Matrix Multiplication Icited by 7
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