Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wil...

Multi-Dimensional Scaling (MDS) is a widely used method for embedding a given distance matrix into a low dimensional space, used both as a preprocessing step for many machine learning problems, as well as a visualization tool in its own right. In this paper, we present an incremental version of MDS (iMDS). In iMDS, d-dimensional data points are presented in a stream, and the task is to embed th...

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In recent years, a number of models of lexical access based on attractor networks have appeared. These models reproduce a number of effects seen in psycholinguistic experiments, but all suffer from unrealistic representations of lexical semantics. In an effort to improve this situation we are looking at techniques developed in the information retrieval literature that use the statistics found i...