In this work, we go beyond these stability results by showing that the LP approximately recovers the MAP solution of a stable instance even after the instance ...

In this work, we go beyond these stability results by showing that the LP approximately recovers the MAP solution of a stable instance even after the instance ...

In this work, we go beyond these stability results by showing that the LP approximately recovers the MAP solution of a stable instance even after the instance ...

This work shows that the LP approximately recovers the MAP solution of a stable instance even after the instance is corrupted by noise, and suggests a new ...

This “noisy stable” model realistically fits with practical MAP inference problems: we design an algorithm for finding “close” stable instances, and show that ...

Sep 7, 2024 · In this work, we go beyond these stability results by showing that the LP approximately recovers the MAP solution of a stable instance even ...

Beyond perturbation stability: LP recovery guarantees for MAP inference on noisy stable instances. Hunter Lang, Aravind Reddy, David Sontag, Aravindan ...

Feb 26, 2021 · Perturbation stability. Several works have given recovery guarantees for the local LP relaxation on perturbation stable instances of uniform ...

Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. Retrieved from https://par.nsf.gov/biblio/10287229 ...

Graph cuts always find a global optimum for Potts models (with a catch) · Beyond perturbation stability: LP recovery guarantees for MAP inference on noisy stable ...