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...
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
Dynamic Parallel Schedules (DPS) is a flow graph based framework for developing parallel applications on clusters of workstations. The DPS flow graph execution model enables automa...
Sebastian Gerlach, Basile Schaeli, Roger D. Hersch
Geographically embedded processes with hidden origins are often observable in events they generate. It is common practice in criminological forensics to reverse simple equation-ba...
—“A General Reflex Fuzzy Min-Max Neural Network” (GRFMN) is presented. GRFMN is capable to extract the underlying structure of the data by means of supervised, unsupervised a...