{"ID":2872886,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.07415","arxiv_id":"2509.07415","title":"EMORF-II: Adaptive EM-based Outlier-Robust Filtering with Correlated Measurement Noise","abstract":"We present a learning-based outlier-robust filter for a general setup where the measurement noise can be correlated. Since it is an enhanced version of EM-based outlier robust filter (EMORF), we call it as EMORF-II. As it is equipped with an additional powerful feature to learn the outlier characteristics during inference along with outlier-detection, EMORF-II has improved outlier-mitigation capability. Numerical experiments confirm performance gains as compared to the state-of-the-art methods in terms of accuracy with an increased computational overhead. However, thankfully the computational complexity order remains at par with other practical methods making it a useful choice for diverse applications.","short_abstract":"We present a learning-based outlier-robust filter for a general setup where the measurement noise can be correlated. Since it is an enhanced version of EM-based outlier robust filter (EMORF), we call it as EMORF-II. As it is equipped with an additional powerful feature to learn the outlier characteristics during infere...","url_abs":"https://arxiv.org/abs/2509.07415","url_pdf":"https://arxiv.org/pdf/2509.07415v1","authors":"[\"Arslan Majal\",\"Aamir Hussain Chughtai\",\"Muhammad Tahir\"]","published":"2025-09-09T05:55:16Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"eess.SP\"]","methods":"[]","has_code":false}