9 citations · 15 across the 5 of their papers we have counts for
5 papers
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems
Rishabh Iyer, Jeff Bilmes
We are motivated by large scale submodular optimization problems, where standard algorithms that treat the submodular functions in the \emph{value oracle model} do not scale. In th…
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs
Rishabh Iyer, Jeff Bilmes
In this paper, we investigate a class of submodular problems which in general are very hard. These include minimizing a submodular cost function under combinatorial constraints, wh…
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance
Vishal Kaushal, Rishabh Iyer, Khoshrav Doctor +6
This paper addresses automatic summarization of videos in a unified manner. In particular, we propose a framework for multi-faceted summarization for extractive, query base and ent…
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking
Rishabh Iyer, Jeff A. Bilmes
We extend the recently introduced theory of Lovasz-Bregman (LB) divergences (Iyer & Bilmes 2012) in several ways. We show that they represent a distortion between a "score" and an…
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications
Rishabh Iyer, Jeff A. Bilmes
We extend the work of Narasimhan and Bilmes [30] for minimizing set functions representable as a dierence between submodular functions. Similar to [30], our new algorithms are guar…