Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Jeff Bilmes

University of Washington

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures

Oct 12, 2020
Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan, Jeff Bilmes, Himanshu Asnani, Rishabh Iyer

* 35 pages, 14 figures, 5 tables 

  Access Paper or Ask Questions

Submodular Combinatorial Information Measures with Applications in Machine Learning

Jul 04, 2020
Rishabh Iyer, Ninad Khargonkar, Jeff Bilmes, Himanshu Asnani


  Access Paper or Ask Questions

Concave Aspects of Submodular Functions

Jun 27, 2020
Rishabh Iyer, Jeff Bilmes

* Also appearing in International Symposium of Information Theory. arXiv admin note: substantial text overlap with arXiv:1506.07329 

  Access Paper or Ask Questions

Data Sketching for Faster Training of Machine Learning Models

Jun 05, 2019
Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec


  Access Paper or Ask Questions

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks

May 27, 2019
Sunil Thulasidasan, Gopinath Chennupati, Jeff Bilmes, Tanmoy Bhattacharya, Sarah Michalak


  Access Paper or Ask Questions

Combating Label Noise in Deep Learning Using Abstention

May 27, 2019
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof

* ICML 2019 

  Access Paper or Ask Questions

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems

Feb 26, 2019
Rishabh Iyer, Jeff Bilmes

* To Appear in Proc. AISTATS 2019 

  Access Paper or Ask Questions

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs

Feb 26, 2019
Rishabh Iyer, Jeff Bilmes

* To Appear in Proc. AISTATS 2019 

  Access Paper or Ask Questions

Stream Clipper: Scalable Submodular Maximization on Stream

Feb 13, 2018
Tianyi Zhou, Jeff Bilmes

* 17 pages, 12 figures, submitted to conference 

  Access Paper or Ask Questions

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation

Aug 16, 2016
Kai Wei, Rishabh Iyer, Shengjie Wang, Wenruo Bai, Jeff Bilmes


  Access Paper or Ask Questions

Scaling Submodular Maximization via Pruned Submodularity Graphs

Jun 01, 2016
Tianyi Zhou, Hua Ouyang, Yi Chang, Jeff Bilmes, Carlos Guestrin


  Access Paper or Ask Questions

Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms

Mar 26, 2016
Stefanie Jegelka, Jeff Bilmes

* 46 pages 

  Access Paper or Ask Questions

On Deep Multi-View Representation Learning: Objectives and Optimization

Feb 02, 2016
Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes


  Access Paper or Ask Questions

Submodular Hamming Metrics

Nov 06, 2015
Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch, Rahul Kidambi, Jeff Bilmes

* 15 pages, 1 figure, a short version of this will appear in the NIPS 2015 conference 

  Access Paper or Ask Questions

Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (2009)

Aug 28, 2014
Jeff Bilmes, Andrew Ng


  Access Paper or Ask Questions

Divide-and-Conquer Learning by Anchoring a Conical Hull

Jun 22, 2014
Tianyi Zhou, Jeff Bilmes, Carlos Guestrin

* 26 pages, long version, in updating 

  Access Paper or Ask Questions

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions

Nov 08, 2013
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

* 21 pages. A shorter version appeared in Advances of NIPS-2013 

  Access Paper or Ask Questions

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints

Nov 08, 2013
Rishabh Iyer, Jeff Bilmes

* 23 pages. A short version of this appeared in Advances of NIPS-2013 

  Access Paper or Ask Questions

Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications

Aug 24, 2013
Rishabh Iyer, Jeff Bilmes

* UAI-2012 
* 17 pages, 8 figures. A shorter version of this appeared in Proc. Uncertainty in Artificial Intelligence (UAI), Catalina Islands, 2012 

  Access Paper or Ask Questions

The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking

Aug 24, 2013
Rishabh Iyer, Jeff Bilmes

* UAI-2013 
* 18 pages. A shorter version appeared in Proc. Uncertainty in Artificial Intelligence (UAI)-2013, Bellevue, WA 

  Access Paper or Ask Questions

Fast Semidifferential-based Submodular Function Optimization

Aug 05, 2013
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

* This work appeared in Proc. International Conference of Machine Learning (ICML, 2013) 

  Access Paper or Ask Questions

Interactive Submodular Set Cover

May 20, 2010
Andrew Guillory, Jeff Bilmes

* 15 pages, 1 figure 

  Access Paper or Ask Questions

Average-Case Active Learning with Costs

May 18, 2009
Andrew Guillory, Jeff Bilmes

* 14 pages, 2 figures 

  Access Paper or Ask Questions