Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Contextual Graphs are a context-based formalism used in various real-world applications. They allow a uniform representation of elements of reasoning and of contexts for describing...
Abstract. Graph constraints were introduced in the area of graph transformation, in connection with the notion of (negative) application conditions, as a form to limit the applicab...
New graph structures where node labels are members of hierarchically organized ontologies or taxonomies have become commonplace in different domains, e.g., life sciences. It is a ...