no code implementations • 10 Mar 2016 • Nathanael Perraudin, Benjamin Ricaud, David Shuman, Pierre Vandergheynst
Accordingly, we suggest a new way to incorporate a notion of locality, and develop local uncertainty principles that bound the concentration of the analysis coefficients of each atom of a localized graph spectral filter frame in terms of quantities that depend on the local structure of the graph around the center vertex of the given atom.
no code implementations • 4 Feb 2014 • Nathanael Perraudin, Vassilis Kalofolias, David Shuman, Pierre Vandergheynst
Convex optimization is an essential tool for machine learning, as many of its problems can be formulated as minimization problems of specific objective functions.
