Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
Segmentation is one of the fundamental components in time series data mining. One of the uses of the time series segmentation is trend analysis - to segment the time series into pr...
Interactive navigation in image-based scenes requires random access to the compressed reference image data. When using state of the art block-based hybrid video coding techniques,...
We introduce a new algorithm for mining sequential patterns. Our algorithm is especially efficient when the sequential patterns in the database are very long. We introduce a novel...
Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Y...
We propose a novel compression method for multiview still images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers character...
Andriy Gelman, Pier Luigi Dragotti, Vladan Velisav...