Sergios Theodoridis

Efficient KLMS and KRLS algorithms: A random fourier feature perspective

2016

We present a new framework for online Least Squares algorithms for nonlinear modeling in RKH spaces (RKHS). Instead of implicitly mapping the data to a RKHS (e.g., kernel trick), we map the data to a …

Nonparametric Bayesian Deep Networks with Local Competition

2018 · arXiv (Cornell University)

The aim of this work is to enable inference of deep networks that retain high accuracy for the least possible model complexity, with the latter deduced from the data during inference. To this end, we …