A generic computational framework for biconvex minimization toolbox in R

Estimations of a large family of statistical models can be casted as optimizing biconvex functions over given (bi)convex sets. Our goal in this project is to develop a generic computational framework for biconvex minimization via the alternating minimization algorithm, including sparse bigraphical models, sparse conditional graphical models and sparse matrix factorization. We describe the design and the implementation plan of our project, and propose a timeline for our development.