nonlinear matrix decomposition

An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU function

  • Nicolas Gillis
  • Margherita Porcelli
  • Giovanni Seraghiti
    • Categories Data Science Algorithms, Optimization in Data Science, Other Topics Tags , ,

    Nonlinear matrix decomposition (NMD) with the ReLU function, denoted ReLU-NMD, is the following problem: given a sparse, nonnegative matrix \(X\) and a factorization rank \(r\), identify a rank-\(r\) matrix \(\Theta\) such that \(X\approx \max(0,\Theta)\). This decomposition finds application in data compression, matrix completion with entries missing not at random, and manifold learning. The standard ReLU-NMD … Read more