About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

• improved optimization of ncut and rcut criterion
• optimized eigenvector initialization
• changed default values for number of runs
• several internal optimizations
• made console output more informative

About: A generalized version of spectral clustering using the graph p-Laplacian.

various internal optimizations

About: A Matlab implementation of Sparse PCA using the inverse power method for nonlinear eigenproblems.

• Added deflation scheme to compute multiple principal components
• Several internal runtime and memory optimizations
• API change: sparsePCA.m is now used to compute multiple components; use computeTradeOffCurve.m to reproduce the examples in the NIPS paper

About: A community detection method based on constrained fractional set programming (CFSP).

Initial Announcement on mloss.org.

About: Matlab code for semi-supervised regression and dimensionality reduction using Hessian energy.

Initial Announcement on mloss.org.

About: The GraphDemo provides Matlab GUIs to explore similarity graphs and their use in machine learning. It aims to highlight the behavior of different kinds of similarity graphs and to demonstrate their [...]

Initial Announcement on mloss.org.