29 citations · 225 across the 32 of their papers we have counts for
7 papers · 1 filter
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-based Active Learning
Kevin Miller, Jeff Calder
We show that uncertainty sampling is sufficient to achieve exploration versus exploitation in graph-based active learning, as long as the measure of uncertainty properly aligns wit…
Ratio convergence rates for Euclidean first-passage percolation: Applications to the graph infinity Laplacian
Leon Bungert, Jeff Calder, Tim Roith
In this paper we prove the first quantitative convergence rates for the graph infinity Laplace equation for length scales at the connectivity threshold. In the graph-based semi-sup…
Use and Misuse of Machine Learning in Anthropology
Jeff Calder, Reed Coil, Annie Melton +3
Machine learning (ML), being now widely accessible to the research community at large, has fostered a proliferation of new and striking applications of these emergent mathematical…
Using machine learning on new feature sets extracted from 3D models of broken animal bones to classify fragments according to break agent
Katrina Yezzi-Woodley, Alexander Terwilliger, Jiafeng Li +4
Distinguishing agents of bone modification at paleoanthropological sites is at the root of much of the research directed at understanding early hominin exploitation of large animal…
The Batch Artifact Scanning Protocol: A new method using computed tomography (CT) to rapidly create three-dimensional models of objects from large collections en masse
Katrina Yezzi-Woodley, Jeff Calder, Mckenzie Sweno +2
Within anthropology, the use of three-dimensional (3D) imaging has become increasingly common and widespread since it broadens the available avenues for addressing a wide range of…
Graph-based Active Learning for Semi-supervised Classification of SAR Data
Kevin Miller, John Mauro, Jason Setiadi +4
We present a novel method for classification of Synthetic Aperture Radar (SAR) data by combining ideas from graph-based learning and neural network methods within an active learnin…