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cs.LG2025
An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU function
Nicolas Gillis, Margherita Porcelli, Giovanni Seraghiti
ReLU matrix decomposition (RMD) is the following problem: given a sparse, nonnegative matrix and a factorization rank , identify a rank- matrix such that $X\approx \m…
cs.LG2023★ 1 cited
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel +4
Mixture models are traditionally represented and learned by adding several distributions as components. Allowing mixtures to subtract probability mass or density can drastically re…