4 papers
VertCoHiRF: Decentralized Vertical Clustering Beyond k-means
Bruno Belucci, Karim Lounici, Vladimir R. Kostic +1
Vertical Federated Learning (VFL) enables collaborative analysis across parties holding complementary feature views of the same samples, yet existing approaches are largely restric…
CoHiRF: Hierarchical Consensus for Interpretable Clustering Beyond Scalability Limits
Katia Meziani, Bruno Belucci, Karim Lounici +1
We introduce CoHiRF (Consensus Hierarchical Random Features), a hierarchical consensus framework that enables existing clustering methods to operate beyond their usual computationa…
kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning
Giacomo Turri, Grégoire Pacreau, Giacomo Meanti +8
kooplearn is a machine-learning library that implements linear, kernel, and deep-learning estimators of dynamical operators and their spectral decompositions. kooplearn can model b…
AdaCap: An Adaptive Contrastive Approach for Small-Data Neural Networks
Bruno Belucci, Karim Lounici, Katia Meziani
Neural networks struggle on small tabular datasets, where tree-based models remain dominant. We introduce Adaptive Contrastive Approach (AdaCap), a training scheme that combines a…