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Finite-Sample Distribution Theory and Efficient Large-Scale Inference for Online Quantile Regression

arXiv:2610.05869v1 Announce Type: new Abstract: This paper studies online quantile regression for large-scale and streaming data using Stochastic SubGradient Descent (SSGD) with constant learning rates. Classical offline inference for quantile regression is computationally and memory intensive. Exi…

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  1. 2026-10-06 04:00 · arXiv stat.ML
    Finite-Sample Distribution Theory and Efficient Large-Scale Inference for Online Quantile Regression

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