NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (19)

cs.LG2013

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

Rishabh Iyer, Jeff Bilmes

stat.ML2014

Divide-and-Conquer Learning by Anchoring a Conical Hull

Tianyi Zhou, Jeff Bilmes, Carlos Guestrin

cs.DS2016

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

Stefanie Jegelka, Jeff Bilmes

cs.LG2019

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs

Rishabh Iyer, Jeff Bilmes

cs.DS2013

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints

Rishabh Iyer, Jeff Bilmes

stat.ML2019

Combating Label Noise in Deep Learning Using Abstention

Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes +2

The paper proposes a loss function that lets deep neural networks abstain from predicting on uncertain or noisy samples, improving robustness to both structured and unstructured la…

#label noise#abstention#deep neural networks#robust learning
cs.AI2014

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

Jeff Bilmes, Andrew Ng

cs.LG2016

Scaling Submodular Maximization via Pruned Submodularity Graphs

Tianyi Zhou, Hua Ouyang, Yi Chang +2

stat.ML2018

Stream Clipper: Scalable Submodular Maximization on Stream

Tianyi Zhou, Jeff Bilmes

cs.DS2013

Fast Semidifferential-based Submodular Function Optimization

Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

cs.DS2013

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions

Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

cs.DS2013

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

Rishabh Iyer, Jeff Bilmes

cs.LG2009

Average-Case Active Learning with Costs

Andrew Guillory, Jeff Bilmes

cs.LG2016

On Deep Multi-View Representation Learning: Objectives and Optimization

Weiran Wang, Raman Arora, Karen Livescu +1

cs.DS2015

Submodular Hamming Metrics

Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch +2

cs.DS2016

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

cs.DM2015

Polyhedral aspects of Submodularity, Convexity and Concavity

Rishabh Iyer, Jeff Bilmes

cs.LG2010

Interactive Submodular Set Cover

Andrew Guillory, Jeff Bilmes

cs.LG2019

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems

Rishabh Iyer, Jeff Bilmes