{"ID":2844420,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.06454","arxiv_id":"2511.06454","title":"Feature weighting for data analysis via evolutionary simulation","abstract":"We analyze an algorithm for assigning weights prior to scalarization in discrete multi-objective problems arising from data analysis. The algorithm evolves weights (interpreted as the relevance of features) by a replicator-type dynamic on the standard simplex, with update indices computed from a normalized data matrix. We prove that the resulting sequence converges globally to a unique interior equilibrium, yielding non-degenerate limiting weights.","short_abstract":"We analyze an algorithm for assigning weights prior to scalarization in discrete multi-objective problems arising from data analysis. The algorithm evolves weights (interpreted as the relevance of features) by a replicator-type dynamic on the standard simplex, with update indices computed from a normalized data matrix....","url_abs":"https://arxiv.org/abs/2511.06454","url_pdf":"https://arxiv.org/pdf/2511.06454v2","authors":"[\"Aris Daniilidis\",\"Alberto Domínguez Corella\",\"Philipp Wissgott\"]","published":"2025-11-09T16:40:47Z","proceeding":"math.OC","tasks":"[\"math.OC\",\"cs.LG\"]","methods":"[]","has_code":false}