166 citations · 1.4k across the 47 of their papers we have counts for
7 papers · 1 filter
Submodular Hamming Metrics
Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch +2
We show that there is a largely unexplored class of functions (positive polymatroids) that can define proper discrete metrics over pairs of binary vectors and that are fairly tract…
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation
Kai Wei, Rishabh Iyer, Shengjie Wang +2
We study two mixed robust/average-case submodular partitioning problems that we collectively call Submodular Partitioning. These problems generalize both purely robust instances of…
Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms
Stefanie Jegelka, Jeff Bilmes
We study an extension of the classical graph cut problem, wherein we replace the modular (sum of edge weights) cost function by a submodular set function defined over graph edges.…
Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes
We investigate three related and important problems connected to machine learning: approximating a submodular function everywhere, learning a submodular function (in a PAC-like set…
Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints
Rishabh Iyer, Jeff Bilmes
We investigate two new optimization problems -- minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular funct…
Fast Semidifferential-based Submodular Function Optimization
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes
We present a practical and powerful new framework for both unconstrained and constrained submodular function optimization based on discrete semidifferentials (sub- and super-differ…