{"ID":2921926,"CreatedAt":"2026-06-02T02:42:49.606572591Z","UpdatedAt":"2026-06-04T00:54:56.190393508Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.01554","arxiv_id":"2606.01554","title":"Fast Near-Optimal Estimation over Symmetric Norm Balls","abstract":"This short note proposes a polynomial-time algorithm for near-optimal Euclidean estimation of a signal constrained to lie in the unit ball of a symmetric norm, where the symmetry is with respect to a known basis and the norm is accessible through an evaluation oracle. We further extend the method to a random-design, moderate-dimensional linear regression setting, where the regression parameter is likewise assumed to belong to a constraint set defined by a symmetric norm.","short_abstract":"This short note proposes a polynomial-time algorithm for near-optimal Euclidean estimation of a signal constrained to lie in the unit ball of a symmetric norm, where the symmetry is with respect to a known basis and the norm is accessible through an evaluation oracle. We further extend the method to a random-design, mo...","url_abs":"https://arxiv.org/abs/2606.01554","url_pdf":"https://arxiv.org/pdf/2606.01554v1","authors":"[\"Matey Neykov\"]","published":"2026-06-01T01:58:28Z","proceeding":"math.ST","tasks":"[\"math.ST\"]","methods":"[]","has_code":false}