I am trying to sample the edges of an undirected graph using weights. The goal is to run a sparsification algorithm on the graph. I see the point that L1 norm is best for sparsification. Can someone tell me how exactly is L1 sampling performed on edges of a graph.
To be more precise with my query, Should we vectorize the indices of the graph and then apply L1 sampling on the sub vectors and perform sparse recovery?(correct me if I am wrong) or is there a better way?
