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The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares(More)
This paper introduces a new robust nonlinear identification algorithm using the predicted residual sums of squares (PRESS) statistic and forward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the(More)
—In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on(More)
Participants' eye-gaze is generally not captured or represented in immersive collaborative virtual environment (ICVE) systems. We present <i>EyeCVE</i>, which uses mobile eye-trackers to drive the gaze of each participant's virtual avatar, thus supporting remote mutual eye-contact and awareness of others' gaze in a perceptually unfragmented shared virtual(More)