A Spectral Approach to Network Design

We present a spectral approach to design approximation algorithms for network problems. observe that the underlying mathematical questions are rounding problems, which were studied in sparsification and discrepancy theory. extend these results incorporate additional non-negative linear constraints, show they can be used significantly scope of problems solved. Our algorithm is an iterative randomized based on regret minimization framework. In some settings, this provides alternative achieve constant factor classical survivable problem, partially answers question Bansal about with concentration property. also many other applications results, including weighted experimental additive sparsification.