Abstract
We introduce a new approach to decomposable submodular function minimization (DSFM) that exploits incidence relations. Incidence relations describe which variables effectively influence the component functions, and when properly utilized, they allow for improving the convergence rates of DSFM solvers. Our main results include the precise parametrization of the DSFM problem based on incidence relations, the development of new scalable alternative projections and parallel coordinate descent methods and an accompanying rigorous analysis of their convergence rates.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2237-2247 |
| Number of pages | 11 |
| Journal | Advances in Neural Information Processing Systems |
| Volume | 2018-December |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 32nd Conference on Neural Information Processing Systems, NeurIPS 2018 - Montreal, Canada Duration: Dec 2 2018 → Dec 8 2018 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing