2 papers
stat.ML2026
ConquerNet: Convolution-Smoothed Quantile ReLU Neural Networks with Minimax Guarantees
Tianpai Luo, Fangwei Wu, Weichi Wu
Quantile regression is a fundamental tool for distributional learning but poses significant optimization challenges for deep models due to the non-smoothness of the pinball loss. W…
math.ST2026
Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
Tianpai Luo, Zhou Zhou
This paper studies simultaneous inference of conditional distributions in nonlinear time series from a sieve M-regression perspective. Existing literature on sieve M-regression has…