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cs.LG2026
Identifiability of Deep Polynomial Neural Networks
Konstantin Usevich, Ricardo Borsoi, Clara Dérand +1
Polynomial Neural Networks (PNNs) possess a rich algebraic and geometric structure. However, their identifiability -- a key property for ensuring interpretability -- remains poorly…
cs.LG2025
Low-Rank Tensor Decompositions for the Theory of Neural Networks
Ricardo Borsoi, Konstantin Usevich, Marianne Clausel
The groundbreaking performance of deep neural networks (NNs) promoted a surge of interest in providing a mathematical basis to deep learning theory. Low-rank tensor decompositions…
cs.LG2024
Personalized Coupled Tensor Decomposition for Multimodal Data Fusion: Uniqueness and Algorithms
Ricardo Augusto Borsoi, Konstantin Usevich, David Brie +1
Coupled tensor decompositions (CTDs) perform data fusion by linking factors from different datasets. Although many CTDs have been already proposed, current works do not address imp…