3 papers
math.ST2026
The Geometry of Statistical Feature Learning in Mean-Field Langevin Dynamics
Zong Shang, Tomoya Wakayama, Guillaume Lecué +1
We introduce a geometric formulation of statistical feature learning for supervised regression. Feature learning is defined through a base--fiber decomposition: the base is the fea…
math.ST2025
Sharp convergence rates for Spectral methods via the feature space decomposition method
Guillaume Lecué, Zhifan Li, Zong Shang
In this paper, we apply the Feature Space Decomposition (FSD) method developed in [LS24, GLS25, LSSW26, ALSS26] to obtain, under fairly general conditions, matching upper and lower…
econ.EM2025
Statistical Inference in Large Multi-way Networks
Lucas Resende, Guillaume Lecué, Lionel Wilner +1
We propose the Polyads estimator, a new method to estimate structural parameters in weighted multi-way networks while controlling for rich, arbitrary structures of fixed effects. T…