A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robus...
Thorsten Bernholt, Robin Nunkesser, Karen Schettli...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Abstract— The accurate estimation of airport capacity is critical for the efficient planning of landing and takeoff operations, and the mitigation of congestion-induced delays. ...
Abstract. We introduce a nonparametric model for sensitivity estimation which relies on generating points similar to the prediction point using its k nearest neighbors. Unlike most...
A common practice when carrying out self-calibration of a camera from one or more views is to start with a guess at the principal point. The general belief is that inaccuracies in...