29 citations · 40 across the 3 of their papers we have counts for
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cs.LG2019★ 5 cited
No-Trick (Treat) Kernel Adaptive Filtering using Deterministic Features
Kan Li, Jose C. Principe
Kernel methods form a powerful, versatile, and theoretically-grounded unifying framework to solve nonlinear problems in signal processing and machine learning. The standard approac…
eess.SP2019
Functional Bayesian Filter
Kan Li, Jose C. Principe
We present a general nonlinear Bayesian filter for high-dimensional state estimation using the theory of reproducing kernel Hilbert space (RKHS). Applying kernel method and the rep…