collaborators

6 papers

cs.LG2026

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…

cs.LG2026

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…

cs.LG2025

Freeze, Diffuse, Decode: Geometry-Aware Adaptation of Pretrained Transformer Embeddings for Antimicrobial Peptide Design

Pankhil Gawade, Adam Izdebski, Myriam Lizotte +4

Pretrained transformers provide rich, general-purpose embeddings, which are transferred to downstream tasks. However, current transfer strategies: fine-tuning and probing, either d…

cs.LG2025

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…

cs.LG2025

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{…

stat.ML2025

Forest Proximities for Time Series

Ben Shaw, Jake Rhodes, Soukaina Filali Boubrahimi +1

RF-GAP has recently been introduced as an improved random forest proximity measure. In this paper, we present PF-GAP, an extension of RF-GAP proximities to proximity forests, an ac…