2 papers
cs.LG2025
FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters
Hiro Ishii, Kenta Niwa, Hiroshi Sawada +3
We propose Federated Preconditioned Mixing (FedPM), a novel Federated Learning (FL) method that leverages second-order optimization. Prior methods--such as LocalNewton, LTDA, and F…
stat.ML2025
KIE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
Hideaki Kim, Tomoharu Iwata, Akinori Fujino
Kernel method-based intensity estimators, formulated within reproducing kernel Hilbert spaces (RKHSs), and classical kernel intensity estimators (KIEs) have been among the most eas…