3 papers
stat.ML2026
Estimating Implicit Regularization in Deep Learning
Joseph H. Rudoler, Kevin Tan, Giles Hooker +1
Deep learning systems are known to exhibit implicit regularization (alt. implicit bias), favoring simple solutions instead of merely minimizing the loss function. In some cases, we…
stat.ML2026
Statistical Inference for Explainable Boosting Machines
Haimo Fang, Kevin Tan, Jonathan Pipping-Gamon +1
Explainable boosting machines (EBMs) are popular "glass-box" models that learn a set of univariate functions using boosting trees. These achieve explainability through visualizatio…
stat.ML2025
Statistical Inference for Gradient Boosting Regression
Haimo Fang, Kevin Tan, Giles Hooker
Gradient boosting is widely popular due to its flexibility and predictive accuracy. However, statistical inference and uncertainty quantification for gradient boosting remain chall…