document: Balanced allocation with succinct representation Motivated by applications in guaranteed delivery in computational advertising , we consider the general problem of balanced allocation in a bipartite supply-demand setting . Our formulation captures the notion of deviation from being balanced by a convex penalty function . While this formulation admits a convex programming solution , we strive for more robust and scalable algorithms . For the case of L1 penalty functions we obtain a simple combinatorial algorithm based on min-cost flow in graphs and show how to precompute a linear amount of information such that the allocation along any edge can be approximated in constant time . We then extend our combinatorial solution to any convex function by solving a convex cost flow . These scalable methods may have applications in other contexts stipulating balanced allocation . We study the performance of our algorithms on large real-world graphs and show that they are efficient , scalable , and robust in practice .
doc_bio_tags: B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O