3 papers
stat.ML2026
Gradient Regularized Newton Boosting Trees with Global Convergence
Nikita Zozoulenko, Daniel Falkowski, Thomas Cass +1
Gradient Boosting Decision Trees (GBDTs) dominate tabular machine learning, with modern implementations like XGBoost, LightGBM, and CatBoost being based on Newton boosting: a secon…
math.NA2025
Numerical Schemes for Signature Kernels
Thomas Cass, Francesco Piatti, Jeffrey Pei
Signature kernels have emerged as a powerful tool within kernel methods for sequential data. In the paper "The Signature Kernel is the solution of a Goursat PDE", the authors ident…
stat.ML2025
Random Feature Representation Boosting
Nikita Zozoulenko, Thomas Cass, Lukas Gonon
We introduce Random Feature Representation Boosting (RFRBoost), a novel method for constructing deep residual random feature neural networks (RFNNs) using boosting theory. RFRBoost…