arXiv AI· Ziyang Wei, Jiaqi Li, Lan Wang, Wei Biao Wu·· 22 小时前评分53
Finite-Sample Distribution Theory and Efficient Large-Scale Inference for Online Quantile Regression
摘要
原文摘录（自动中文摘要暂不可用）：Finite-Sample Distribution Theory and Efficient Large-Scale Inference for Online Quantile Regression 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. Existing wo
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来源：arXiv AI · arxiv.org