activity
20122018
most citedParallel implementation of fast randomized algorithms for the decomposition of low rank matrices

7 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

math-ph2018

Finding Exact Forms on Thermodynamic Manifolds

Chao Ju, Mark Stalzer

Because only two variables are needed to characterize a simple thermodynamic system in equilibrium, any such system is constrained on a 2D manifold. Of particular interest are the…

stat.ML2017★ 3 cited

Bayesian Optimization for Parameter Tuning of the XOR Neural Network

Lawrence Stewart, Mark Stalzer

When applying Machine Learning techniques to problems, one must select model parameters to ensure that the system converges but also does not become stuck at the objective function…

cs.AI2017

TheoSea: Marching Theory to Light

Mark A. Stalzer, Chao Ju

There is sufficient information in the far-field of a radiating dipole antenna to rediscover the Maxwell Equations and the wave equations of light, including the speed of light $c.…

cs.LG2017★ 1 cited

Deriving Compact Laws Based on Algebraic Formulation of a Data Set

Wenqing Xu, Mark Stalzer

In various subjects, there exist compact and consistent relationships between input and output parameters. Discovering the relationships, or namely compact laws, in a data set is o…

cs.AI2017★ 1 cited

On the enumeration of sentences by compactness

Mark A. Stalzer

Presented is a Julia meta-program that discovers compact theories from data if they exist. It writes candidate theories in Julia and then validates: tossing the bad theories and ke…

cs.DL2015★ 1 cited

A Preliminary Review of Influential Works in Data-Driven Discovery

Mark Stalzer, Chris Mentzel

The Gordon and Betty Moore Foundation ran an Investigator Competition as part of its Data-Driven Discovery Initiative in 2014. We received about 1,100 applications and each applica…

cs.DC2012★ 7 cited

Parallel implementation of fast randomized algorithms for the decomposition of low rank matrices

Andrew Lucas, Mark Stalzer, John Feo

We analyze the parallel performance of randomized interpolative decomposition by decomposing low rank complex-valued Gaussian random matrices up to 64 GB. We chose a Cray XMT super…