Search Results for author: Rishabh K. Iyer

Found 3 papers, 0 papers with code

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications

no code implementations NeurIPS 2015 Kai Wei, Rishabh K. Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes

In the present paper, we bridge this gap, by proposing several new algorithms (including greedy, majorization-minimization, minorization-maximization, and relaxation algorithms) that not only scale to large datasets but that also achieve theoretical approximation guarantees comparable to the state-of-the-art.

Clustering Distributed Optimization +3

Learning Mixtures of Submodular Functions for Image Collection Summarization

no code implementations NeurIPS 2014 Sebastian Tschiatschek, Rishabh K. Iyer, Haochen Wei, Jeff A. Bilmes

This paper provides, to our knowledge, the first systematic approach for quantifying the problem of image collection summarization, along with a new dataset of image collections and human summaries.

Document Summarization Structured Prediction

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints

no code implementations NeurIPS 2013 Rishabh K. Iyer, Jeff A. Bilmes

We are motivated by a number of real-world applications in machine learning including sensor placement and data subset selection, which require maximizing a certain submodular function (like coverage or diversity) while simultaneously minimizing another (like cooperative cost).

Cannot find the paper you are looking for? You can Submit a new open access paper.