GSPBOX: A toolbox for signal processing on graphs

This document introduces the Graph Signal Processing Toolbox (GSPBox) a framework that can be used to tackle graph related problems with a signal processing approach. It explains the structure and the organization of this software. It also contains a general description of the important modules.

[1]  Pierre Vandergheynst,et al.  A Multiscale Pyramid Transform for Graph Signals , 2013, IEEE Transactions on Signal Processing.

[2]  M. Randic,et al.  Resistance distance , 1993 .

[3]  M. Rudelson Random Vectors in the Isotropic Position , 1996, math/9608208.

[4]  Fan Zhang,et al.  Graph spectral image smoothing using the heat kernel , 2008, Pattern Recognit..

[5]  B. Schölkopf,et al.  A Regularization Framework for Learning from Graph Data , 2004, ICML 2004.

[6]  Fan Chung,et al.  Spectral Graph Theory , 1996 .

[7]  Florian Dörfler,et al.  Kron Reduction of Graphs With Applications to Electrical Networks , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Pierre Vandergheynst,et al.  Vertex-Frequency Analysis on Graphs , 2013, ArXiv.

[9]  Pierre Vandergheynst,et al.  Spectrum-Adapted Tight Graph Wavelet and Vertex-Frequency Frames , 2013, IEEE Transactions on Signal Processing.

[10]  Gilbert Strang,et al.  The Discrete Cosine Transform , 1999, SIAM Rev..

[11]  Isaac Z. Pesenson,et al.  Variational Splines and Paley–Wiener Spaces on Combinatorial Graphs , 2009, ArXiv.

[12]  Mark Rudelson,et al.  Sampling from large matrices: An approach through geometric functional analysis , 2005, JACM.

[13]  Pascal Frossard,et al.  The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains , 2012, IEEE Signal Processing Magazine.

[14]  Bernhard Schölkopf,et al.  Learning with Local and Global Consistency , 2003, NIPS.

[15]  Bernhard Schölkopf,et al.  Learning from labeled and unlabeled data on a directed graph , 2005, ICML.

[16]  Pierre Vandergheynst,et al.  Wavelets on Graphs via Spectral Graph Theory , 2009, ArXiv.

[17]  Pierre Vandergheynst,et al.  UNLocBoX A matlab convex optimization toolbox using proximal splitting methods , 2014, ArXiv.

[18]  P. Vandergheynst,et al.  Accelerated filtering on graphs using Lanczos method , 2015, 1509.04537.

[19]  Marc Levoy,et al.  Zippered polygon meshes from range images , 1994, SIGGRAPH.

[20]  David G. Lowe,et al.  Scalable Nearest Neighbor Algorithms for High Dimensional Data , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Mikhail Belkin,et al.  Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples , 2006, J. Mach. Learn. Res..

[22]  Pierre Vandergheynst,et al.  A windowed graph Fourier transform , 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

[23]  Sunil K. Narang,et al.  Graph-wavelet filterbanks for edge-aware image processing , 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

[24]  Pierre Vandergheynst,et al.  A Framework for Multiscale Transforms on Graphs , 2013, arXiv.org.

[25]  Nikhil Srivastava,et al.  Graph sparsification by effective resistances , 2008, SIAM J. Comput..