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New Quantizer Optimizes Output Distribution and Minimizes Error

Researchers have developed an optimal quantizer for real-valued random variables, ensuring the output distribution matches a specified target while minimizing estimation error. The method involves a permutation of output values and utilizes the cumulative distribution function. This technique is beneficial for controlling output entropy, maximizing mutual information, and tailoring distributions for communication or anonymization. AI

RANK_REASON This is a research paper detailing a new mathematical method for quantization. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.AI →

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Aolin Xu ·

    Minimum Distortion Quantization with Specified Output Distribution

    arXiv:2606.10458v1 Announce Type: cross Abstract: We derive the optimal quantizer of a real-valued random variable $W$ with distribution $P_W$ such that 1) the distribution of the quantization output $X$ that can take $k$ values follows any specified distribution $P_X$ over $\{1,…