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Most of graph-based methods for semi-supervised learning are transductive, giving predictions for only the unlabeled data in the training set, and not for an arbitrary test point. SLC (Semi-supervised Local Linear Coordinate), which is based on LLC (Local Linear Coordinate) is present here as an inductive method. The mixture of factor analyzers is used to model the raw data set, and the label smoothness...
This article presents a study of Gaussian process (GP) models applied to the problems of modeling and data fusion in the context of large-scale terrain modeling. The proposed model naturally provides a multiresolution representation of space, incorporates and handles uncertainties aptly, and copes with incompleteness of sensory information. These attributes are considered essential to support most...
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