970 citations · 3k across the 88 of their papers we have counts for
5 papers · 1 filter
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets
Adarsh Prasad, Stefanie Jegelka, Dhruv Batra
To cope with the high level of ambiguity faced in domains such as Computer Vision or Natural Language processing, robust prediction methods often search for a diverse set of high-q…
Weakly-supervised Discovery of Visual Pattern Configurations
Hyun Oh Song, Yong Jae Lee, Stefanie Jegelka +1
The increasing prominence of weakly labeled data nurtures a growing demand for object detection methods that can cope with minimal supervision. We propose an approach that automati…
On the Convergence Rate of Decomposable Submodular Function Minimization
Robert Nishihara, Stefanie Jegelka, Michael I. Jordan
Submodular functions describe a variety of discrete problems in machine learning, signal processing, and computer vision. However, minimizing submodular functions poses a number of…
On learning to localize objects with minimal supervision
Hyun Oh Song, Ross Girshick, Stefanie Jegelka +3
Learning to localize objects with minimal supervision is an important problem in computer vision, since large fully annotated datasets are extremely costly to obtain. In this paper…
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.…