In many regression tasks, in addition to an accurate estimate of the conditional mean of the target distribution, an indication of the predictive uncertainty is also required. Ther...
Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chap...
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...