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cs.IR2024★ 3 cited
Early Exit Strategies for Approximate k-NN Search in Dense Retrieval
Francesco Busolin, Claudio Lucchese, Franco Maria Nardini +3
Learned dense representations are a popular family of techniques for encoding queries and documents using high-dimensional embeddings, which enable retrieval by performing approxim…
cs.IR2021
Learning Early Exit Strategies for Additive Ranking Ensembles
Francesco Busolin, Claudio Lucchese, Franco Maria Nardini +3
Modern search engine ranking pipelines are commonly based on large machine-learned ensembles of regression trees. We propose LEAR, a novel - learned - technique aimed to reduce the…