This post is about summary of a talk by Federico Monti on "Deep Geometric Matrix Completion". It is a second post in a series of four posts. The first post discusses about a talk by Xavier Bresson at IPAM UCLA workshop : Link to first post . IPAM recently hosted a workshop on New Deep Learning Techniques . This blog is about a talk at the workshop by Federico Monti on Deep Geometric Matrix Completion . Deep Geometric Matrix Completion is a geometric deep learning based approach for Recommendation Systems . The problem of recommending an item to customers can be formulated as a matrix completion task. Matrix completion as a constraint minimization problem: Many researchers have posed a matrix completion problem as constraint minimization problem. Candes et al, 2008 proposed a method that reconstructs a matrix \(X\) which is as close to the original user-item matrix as possible. The method puts additional low rank constraint on the matrix that acts as a r...