4 citations · 11 across the 7 of their papers we have counts for
8 papers
Multi-Period Max Flow Network Interdiction with Restructuring for Disrupting Domestic Sex Trafficking Networks
Daniel Kosmas, Thomas C Sharkey, John E Mitchell +2
We consider a new class of multi-period network interdiction problems, where interdiction and restructuring decisions are decided upon before the network is operated and implemente…
Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers
April Sagan, John E. Mitchell
This paper considers a large class of problems where we seek to recover a low rank matrix and/or sparse vector from some set of measurements. While methods based on convex relaxati…
Optimizing Edge Sets in Networks to Produce Ground Truth Communities Based on Modularity
Daniel Kosmas, John E. Mitchell, Thomas C. Sharkey +1
We consider two new problems regarding the impact of edge addition or removal on the modularity of partitions (or community structures) in a network. The first problem seeks to add…
Interdicting Restructuring Networks with Applications in Illicit Trafficking
Daniel Kosmas, Thomas C. Sharkey, John E. Mitchell +2
We consider a new class of max flow network interdiction problems, where the defender is able to introduce new arcs to the network after the attacker has made their interdiction de…
Training Deep Neural Networks with Constrained Learning Parameters
Prasanna Date, Christopher D. Carothers, John E. Mitchell +2
Today's deep learning models are primarily trained on CPUs and GPUs. Although these models tend to have low error, they consume high power and utilize large amount of memory owing…
Low-Rank Factorization for Rank Minimization with Nonconvex Regularizers
April Sagan, John E. Mitchell
Rank minimization is of interest in machine learning applications such as recommender systems and robust principal component analysis. Minimizing the convex relaxation to the rank…
Solving Linear Programs with Complementarity Constraints using Branch-and-Cut
Bin Yu, John E. Mitchell, Jong-Shi Pang
A linear program with linear complementarity constraints (LPCC) requires the minimization of a linear objective over a set of linear constraints together with additional linear com…
A Penalty Method for Rank Minimization Problems in Symmetric Matrices
Xin Shen, John E. Mitchell
The problem of minimizing the rank of a symmetric positive semidefinite matrix subject to constraints can be cast equivalently as a semidefinite program with complementarity constr…