A nonconvex l1/2-regularized nonnegative matrix factorization method with ADMM solver and detection estimation improves sparse network recovery under imperfect observations compared to baselines.
Structured low-rank matrix fac- torization: Optimality, algorithm, and applications to image processing,
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Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks
A nonconvex l1/2-regularized nonnegative matrix factorization method with ADMM solver and detection estimation improves sparse network recovery under imperfect observations compared to baselines.