Section: New Results
Active-set Methods for Submodular Optimization
Participants : K. S. Sesh Kumar [correspondent] , Francis Bach.
In [46] , we consider submodular optimization problems such as submodular function minimization (SFM) and quadratic problems regularized by the Lovász extension; for cut functions, this corresponds respectively to graph cuts and total variation (TV) denoising. Given a submodular function with an SFM oracle, we propose a new active-set algorithm for total variation denoising, which is more flexible than existing ones; the algorithm may be seen as a local descent algorithm over ordered partitions with explicit convergence guarantees. For functions that decompose into the sum of two functions