2 papers
math.NA2026
Computing the Nonnegative Low-Rank Leading Eigenmatrix and its Applications to Markov Grids and Metzler Operators
Nicolas Gillis, Carmela Scalone
We consider in this paper the problem of computing a nonnegative low-rank approximation of the rightmost eigenpair of a linear matrix-valued real operator. We propose an algorithm…
cs.LG2025
Explicit Group Sparse Projection with Applications to Deep Learning and NMF
Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso +3
We design a new sparse projection method for a set of vectors that guarantees a desired average sparsity level measured leveraging the popular Hoyer measure (an affine function of…