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 701–725 of 753 papers

Title	Date	Tasks	Status
Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs	Nov 2, 2018	Graph RankingKnowledge Graphs	CodeCode Available
Hashing as Tie-Aware Learning to Rank	May 23, 2017	Image RetrievalLearning-To-Rank	CodeCode Available
Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture	Jul 20, 2017	Feature EngineeringLearning-To-Rank	CodeCode Available
Combinatorial Logistic Bandits	Oct 22, 2024	Computational EfficiencyLearning-To-Rank	CodeCode Available
Learning to Rank Rationales for Explainable Recommendation	Jun 10, 2022	Explainable RecommendationLearning-To-Rank	CodeCode Available
Rank Pooling for Action Recognition	Dec 6, 2015	Action RecognitionGesture Recognition	CodeCode Available
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams	Jan 2, 2019	Learning-To-RankReinforcement Learning	CodeCode Available
Optimization of Decision Tree Evaluation Using SIMD Instructions	May 15, 2022	BinarizationCPU	CodeCode Available
Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank	Jun 25, 2025	Learning-To-Rank	CodeCode Available
Optimizing Group-Fair Plackett-Luce Ranking Models for Relevance and Ex-Post Fairness	Aug 25, 2023	FairnessLearning-To-Rank	CodeCode Available
MGL2Rank: Learning to Rank the Importance of Nodes in Road Networks Based on Multi-Graph Fusion	May 20, 2023	DiversityGraph Learning	CodeCode Available
SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval	Dec 12, 2019	Information RetrievalLearning-To-Rank	CodeCode Available
Learning to Rank Using Localized Geometric Mean Metrics	May 22, 2017	Computational EfficiencyLearning-To-Rank	CodeCode Available
ShaRP: A Novel Feature Importance Framework for Ranking	Jan 30, 2024	Feature ImportanceLearning-To-Rank	CodeCode Available
Distance-based Positive and Unlabeled Learning for Ranking	May 20, 2020	Learning-To-RankSpecificity	CodeCode Available
A Probabilistic Position Bias Model for Short-Video Recommendation Feeds	Jul 26, 2023	Learning-To-RankPosition	CodeCode Available
Learning to Rank Visual Stories From Human Ranking Data	May 1, 2022	Learning-To-RankText Generation	CodeCode Available
Overcoming Prior Misspecification in Online Learning to Rank	Jan 25, 2023	Learning-To-Rank	CodeCode Available
Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm	Sep 16, 2018	Learning-To-RankPosition	CodeCode Available
PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer	Feb 28, 2021	Learning-To-Rank	CodeCode Available
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective	Jun 13, 2023	Learning-To-RankOffline RL	CodeCode Available
Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank	Mar 31, 2022	counterfactualGeneral Reinforcement Learning	CodeCode Available
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance	Sep 6, 2019	Learning-To-Rank	CodeCode Available
Learning to Rank Words: Optimizing Ranking Metrics for Word Spotting	Jun 9, 2021	Learning-To-RankRetrieval	CodeCode Available
Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset	Apr 3, 2024	Learning-To-Rank	CodeCode Available

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