4 papers
Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment
Adrien Aumon, Myriam Lizotte, Guy Wolf +2
Label-supervised manifold alignment bridges the gap between unsupervised and correspondence-based paradigms by leveraging shared label information to align multimodal datasets. Sti…
Revisiting Forest Proximities via Sparse Leaf-Incidence Kernels
Adrien Aumon, Guy Wolf, Kevin R. Moon +1
Decision forests induce supervised similarities through the partition structure of their trees. Yet forest proximity computation is still often treated as a quadratic operation in…
Random Forest Autoencoders for Guided Representation Learning
Adrien Aumon, Shuang Ni, Myriam Lizotte +3
Extensive research has produced robust methods for unsupervised data visualization. Yet supervised visualization$\unicode{x2013}$where expert labels guide representations$\unicode{…
Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension
Shuang Ni, Adrien Aumon, Guy Wolf +2
The value of supervised dimensionality reduction lies in its ability to uncover meaningful connections between data features and labels. Common dimensionality reduction methods emb…