3 papers
stat.ML2026
Stochastic Gradient Descent: A Nonlinear Time Series Perspective
Jiaqi Li, Zhipeng Lou, Stefan Richter +1
This paper investigates the statistical behavior of Stochastic Gradient Descent (SGD) with constant step size under the framework of iterated random functions. Compared to previous…
stat.ML2026
Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
Soham Bonnerjee, Zhipeng Lou, Wei Biao Wu
Despite the sustained popularity of Q-learning as a practical tool for policy determination, a majority of relevant theoretical literature deals with either constant ($η_{t}\equiv…
stat.ML2025
Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
Jiaqi Li, Zhipeng Lou, Johannes Schmidt-Hieber +1
Stochastic Gradient Descent (SGD) and its Ruppert-Polyak averaged variant (ASGD) lie at the heart of modern large-scale learning, yet their theoretical properties in high-dimension…