activity
20162023
most citedDoing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing

23 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

math.OC2023

Heuristic Algorithms for Placing Geomagnetically Induced Current Blocking Devices

Minseok Ryu, Ahmed Attia, Arthur Barnes +3

We propose a new heuristic approach for solving the challenge of determining optimal placements for geomagnetically induced current blocking devices on electrical grids. Traditiona…

math.OC2023

Robust A-Optimal Experimental Design for Bayesian Inverse Problems

Ahmed Attia, Sven Leyffer, Todd Munson

Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian i…

math.OC2023

Polytopic Superset Algorithm for Nonlinear Robust Optimization

Bowen Li, Kibaek Kim, Sven Leyffer

Nonlinear robust optimization (NRO) is widely used in different applications, including energy, control, and economics, to make robust decisions under uncertainty. One of the class…

math.OC20226 cited

Compact representations of structured BFGS matrices

Johannes J. Brust, Zichao, Di +2

For general large-scale optimization problems compact representations exist in which recursive quasi-Newton update formulas are represented as compact matrix factorizations. For pr…

cs.OH201623 cited

Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing

Sven Leyffer, Stefan M. Wild, Mike Fagan +4

Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness, where the quality of the solution can be traded for energy savings, has b…