1 citations · 1 across the 4 of their papers we have counts for
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The Generalized Proximity Forest
Ben Shaw, Adam Rustad, Sofia Pelagalli Maia +2
Recent work has demonstrated the utility of Random Forest (RF) proximities for various supervised machine learning tasks, including outlier detection, missing data imputation, and…
Guided Manifold Alignment with Geometry-Regularized Twin Autoencoders
Jake S. Rhodes, Adam G. Rustad, Marshall S. Nielsen +3
Manifold alignment (MA) involves a set of techniques for learning shared representations across domains, yet many traditional MA methods are incapable of performing out-of-sample e…
Random Forest-Supervised Manifold Alignment
Jake S. Rhodes, Adam G. Rustad
Manifold alignment is a type of data fusion technique that creates a shared low-dimensional representation of data collected from multiple domains, enabling cross-domain learning a…