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We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
We consider the following problem known as simultaneous geometric graph embedding (SGE). Given a set of planar graphs on a shared vertex set, decide whether the vertices can be pla...
Alejandro Estrella-Balderrama, Elisabeth Gassner, ...
Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for ins...
Miquel Ferrer, Ernest Valveny, Francesc Serratosa,...