collaborators

1 paper

cs.IR2026

LO-FAR: A Cost-Aware Local Filter for Sparse Feature Ranking in Industrial Ad Recommendation

Egemen Erbayat, Luis Duque, Sohini Roychowdhury +2

Industrial ad recommendation models rely heavily on sparse, high-cardinality ID-list features that encode user histories and contextual identifiers. Each is backed by a dedicated e…