Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function opt...
Daniel J. Lizotte, Tao Wang, Michael H. Bowling, D...
Given the facial points extracted from an image of a face in an arbitrary pose, the goal of facial-point-based headpose normalization is to obtain the corresponding facial points ...
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...
Abstract— Artificial neural networks have proved an attractive approach to non-linear regression problems arising in environmental modelling, such as statistical downscaling, sh...
Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Do...