3 papers
stat.ML2025
Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)
Biprateep Dey, David Zhao, Brett H. Andrews +3
Key science questions, such as galaxy distance estimation and weather forecasting, often require knowing the full predictive distribution of a target variable given complex inp…
math.ST2024
The e-value and the Full Bayesian Significance Test: Logical Properties and Philosophical Consequences
Julio Michael Stern, Carlos Alberto de Braganca Pereira, Marcelo de Souza Lauretto +5
This article gives a conceptual review of the e-value, ev(H|X) -- the epistemic value of hypothesis H given observations X. This statistical significance measure was developed in o…
stat.ML2024
RFFNet: Large-Scale Interpretable Kernel Methods via Random Fourier Features
Mateus P. Otto, Rafael Izbicki
Kernel methods provide a flexible and theoretically grounded approach to nonlinear and nonparametric learning. While memory and run-time requirements hinder their applicability to…