Jagdeep Pani

Non-negative Matrix Factorization under Heavy Noise

The Noisy Non-negative Matrix factorization (NMF) is: given a data matrix A (d x n), find non-negative matrices B;C (d x k, k x n respy.) so that A = BC +N, where N is a noise matrix. Existing polynomial time algorithms with proven error guarantees require EACH column N_⋅j to have l1 norm much small…