59 citations · 99 across the 12 of their papers we have counts for
12 papers
Revisiting Sparse Matrix Coloring and Bicoloring
Alexis Montoison, Guillaume Dalle, Assefaw Gebremedhin
Sparse matrix coloring and bicoloring are fundamental building blocks of sparse automatic differentiation. Bicoloring is particularly advantageous for rectangular Jacobian matrices…
Facets of Disparate Impact: Evaluating Legally Consistent Bias in Machine Learning
Jarren Briscoe, Assefaw Gebremedhin
Leveraging current legal standards, we define bias through the lens of marginal benefits and objective testing with the novel metric "Objective Fairness Index". This index combines…
Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
Jarren Briscoe, Garrett Kepler, Daryl Deford +1
Evaluating machine learning models is crucial not only for determining their technical accuracy but also for assessing their potential societal implications. While the potential fo…
High-order Line Graphs of Non-uniform Hypergraphs: Algorithms, Applications, and Experimental Analysis
Xu T. Liu, Jesun Firoz, Sinan Aksoy +5
Hypergraphs offer flexible and robust data representations for many applications, but methods that work directly on hypergraphs are not readily available and tend to be prohibitive…
Reinforcement Learning for Battery Energy Storage Dispatch augmented with Model-based Optimizer
Gayathri Krishnamoorthy, Anamika Dubey
Reinforcement learning has been found useful in solving optimal power flow (OPF) problems in electric power distribution systems. However, the use of largely model-free reinforceme…
Parallel Algorithms and Heuristics for Efficient Computation of High-Order Line Graphs of Hypergraphs
Xu T. Liu, Jesun Firoz, Andrew Lumsdaine +4
This paper considers structures of systems beyond dyadic (pairwise) interactions and investigates mathematical modeling of multi-way interactions and connections as hypergraphs, wh…
Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy
Yunshu Du, Garrett Warnell, Assefaw Gebremedhin +2
Experience replay (ER) improves the data efficiency of off-policy reinforcement learning (RL) algorithms by allowing an agent to store and reuse its past experiences in a replay bu…
Fast Algorithms for the Maximum Clique Problem on Massive Graphs with Applications to Overlapping Community Detection
Bharath Pattabiraman, Md. Mostofa Ali Patwary, Assefaw H. Gebremedhin +2
The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, information retrieval and many other areas related to the World Wide…
Parallel Maximum Clique Algorithms with Applications to Network Analysis and Storage
Ryan A. Rossi, David F. Gleich, Assefaw H. Gebremedhin +1
We propose a fast, parallel maximum clique algorithm for large sparse graphs that is designed to exploit characteristics of social and information networks. The method exhibits a r…
What if CLIQUE were fast? Maximum Cliques in Information Networks and Strong Components in Temporal Networks
Ryan A. Rossi, David F. Gleich, Assefaw H. Gebremedhin +1
Exact maximum clique finders have progressed to the point where we can investigate cliques in million-node social and information networks, as well as find strongly connected compo…
Fast Algorithms for the Maximum Clique Problem on Massive Sparse Graphs
Bharath Pattabiraman, Md. Mostofa Ali Patwary, Assefaw H. Gebremedhin +2
The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, informatics, and many other areas. Although there exist several algor…
Graph Coloring Algorithms for Muti-core and Massively Multithreaded Architectures
Umit Catalyurek, John Feo, Assefaw Gebremedhin +2
We explore the interplay between architectures and algorithm design in the context of shared-memory platforms and a specific graph problem of central importance in scientific and h…