2026
Learning to Rank from Incomplete Rankings
ICML 2026poster
In domains such as recommender systems and information retrieval, learning from human-generated feedback is especially challenging because the information provided is often sparse and incomplete. In this work, we address the problem of learning the top-$k$ items from incomplete rankings. Most existi…