2 papers
stat.ML2026
Central Limit Theorems for Stochastic Gradient Descent Quantile Estimators
Ziyang Wei, Jiaqi Li, Likai Chen +1
This paper develops asymptotic theory for quantile estimation via stochastic gradient descent (SGD) with a constant learning rate. The quantile loss function is neither smooth nor…
stat.ML2025
Smoothed SGD for quantiles: Bahadur representation and Gaussian approximation
Likai Chen, Georg Keilbar, Wei Biao Wu
This paper considers the estimation of quantiles via a smoothed version of the stochastic gradient descent (SGD) algorithm. By smoothing the score function in the conventional SGD…