Author

C. C. Cavalcante

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#machine learning Preprint Sep 2026

Gromov-Wasserstein Distillation for Inductive Multi-View Embedding

Gromov-Wasserstein multidimensional scaling (GW-MDS) learns low-dimensional representations from relational data but remains transductive, providing no explicit mapping for unseen samples. We introduce an inductive framework based on barycentric distillation. A GW-MDS teacher learns a latent support and an optimal tran...

Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, C. C. Cavalcante · 0 citations

#machine learning Preprint Sep 2026

Multi-Domain Clustering via Measure Quantization

This work presents a general framework for multi-domain clustering via measure quantization: given samples from multiple domains, given samples from multiple domains, they learn a shared set of cluster prototypes by minimizing a probability metric between each domain's probability measure and the measure of prototypes.

Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, C. C. Cavalcante · 0 citations