In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Abstract. The sequential regularization method is a reformulation of the unsteady Navier-Stokes equations from the view point of constrained dynamical systems or approximate Helmho...
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
: In this paper we obtain new effective results on the Halpern iterations of nonexpansive mappings using methods from mathematical logic or, more specifically, proof-theoretic te...
— Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper, we extend the regularized channel inversion techniq...
Heunchul Lee, Kwangwon Lee, Bertrand M. Hochwald, ...