The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
— Many important applications are organized around long-lived, irregular sparse graphs (e.g., data and knowledge bases, CAD optimization, numerical problems, simulations). The gr...
Michael DeLorimier, Nachiket Kapre, Nikil Mehta, D...
Graph based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems. A crucial step in graph based SSL methods is the conv...
GXL (Graph eXchange Language) is designed to be a standard exchange format for graph-based tools. GXL is defined as an XML sublanguage, which offers support for exchanging instanc...