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Learning-To-Rank

Learning to rank is the application of machine learning to build ranking models. Some common use cases for ranking models are information retrieval (e.g., web search) and news feeds application (think Twitter, Facebook, Instagram).

Papers

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Showing 131–140 of 753 papers

Title	Date	Tasks	Status	Score
Improving Pairwise Ranking for Multi-label Image Classification	Apr 11, 2017	ClassificationGeneral Classification	CodeCode Available	5
Intersection of Parallels as an Early Stopping Criterion	Aug 19, 2022	counterfactualLearning-To-Rank	CodeCode Available	5
Learning to rank for censored survival data	Jun 6, 2018	Learning-To-RankSurvival Analysis	CodeCode Available	5
Autoregressive Reasoning over Chains of Facts with Transformers	Dec 17, 2020	Learning-To-Rank	CodeCode Available	5
How to Forget Clients in Federated Online Learning to Rank?	Jan 24, 2024	Learning-To-Rank	CodeCode Available	5
Automatic Quality Estimation for Natural Language Generation: Ranting (Jointly Rating and Ranking)	Oct 10, 2019	Learning-To-RankText Generation	CodeCode Available	5
Hashing as Tie-Aware Learning to Rank	May 23, 2017	Image RetrievalLearning-To-Rank	CodeCode Available	5
Hidden or Inferred: Fair Learning-To-Rank with Unknown Demographics	Jul 24, 2024	AttributeFairness	CodeCode Available	5
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank	Sep 27, 2023	Learning-To-Rank	CodeCode Available	5
Groupwise Query Performance Prediction with BERT	Apr 25, 2022	Learning-To-RankPrediction	CodeCode Available	5

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