We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
In this paper, we apply supershapes and R-functions to surface recovery from 3D data sets. Individual supershapes are separately recovered from a segmented mesh. R-functions are u...
Abstract. Image segmentation in microscopy, especially in interferencebased optical microscopy modalities, is notoriously challenging due to inherent optical artifacts. We propose ...
Given a set of N multi-dimensional points, we study the computation of -quantiles according to a ranking function F, which is provided by the user at runtime. Specifically, F compu...
In distributed systems, transcoding techniques have been used to customize multimedia objects, utilizing trade-offs between the quality and sizes of these objects to provide diffe...