2 papers
cs.LG2026
Dynamic Regret for Online Regression in RKHS via Discounted VAW and Subspace Approximation
Dmitry B. Rokhlin, Georgiy A. Karapetyants
We study online regression with the square loss in a reproducing kernel Hilbert space under a dynamic regret criterion. The learner is compared with a time-varying comparator seque…
cs.LG2025
A hierarchical Vovk-Azoury-Warmuth forecaster with discounting for online regression in RKHS
Dmitry B. Rokhlin
We study the problem of online regression with the unconstrained quadratic loss against a time-varying sequence of functions from a Reproducing Kernel Hilbert Space (RKHS). Recentl…