We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
New emerging scientific applications in geosciences, sensor and spatio-temporal domains require adaptive analysis frameworks that can handle large datasets with multiple dimension...
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...
Urban planners are dealing with problems of urban sprawl and CO2 emissions. The multidimensional character of these phenomena requires new analysis and visualization tools that ar...
Sebastian Petsch, Subhrajit Guhathakurta, Hans Hag...
Background: Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integra...
R. Brent Calder, Rudolf B. Beems, Harry van Steeg,...