{"ID":2828701,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.14932","arxiv_id":"2512.14932","title":"Low-rank MMSE filters, Kronecker-product representation, and regularization: a new perspective","abstract":"In this work, we propose a method to efficiently find the regularization parameter for low-rank MMSE filters based on a Kronecker-product representation. We show that the regularization parameter is surprisingly linked to the problem of rank selection and, thus, properly choosing it, is crucial for low-rank settings. The proposed method is validated through simulations, showing significant gains over commonly used methods.","short_abstract":"In this work, we propose a method to efficiently find the regularization parameter for low-rank MMSE filters based on a Kronecker-product representation. We show that the regularization parameter is surprisingly linked to the problem of rank selection and, thus, properly choosing it, is crucial for low-rank settings. T...","url_abs":"https://arxiv.org/abs/2512.14932","url_pdf":"https://arxiv.org/pdf/2512.14932v1","authors":"[\"Daniel Gomes de Pinho Zanco\",\"Leszek Szczecinski\",\"Jacob Benesty\",\"Eduardo Vinicius Kuhn\"]","published":"2025-12-16T21:54:06Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false}