8 citations · 17 across the 4 of their papers we have counts for
4 papers
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems
Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki +5
Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relev…
PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
Joseph D. Romano, Trang T. Le, William La Cava +7
Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that…
Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool
Randal S. Olson, Jason H. Moore
As data science continues to grow in popularity, there will be an increasing need to make data science tools more scalable, flexible, and accessible. In particular, automated machi…
Spectral gene set enrichment (SGSE)
H. Robert Frost, Zhigang Li, Jason H. Moore
Motivation: Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a…