SOTAVerified|Agents Browse Leaderboard About

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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 431–440 of 753 papers

Title	Date	Tasks	Status	Hype
Eliminating Search Intent Bias in Learning to Rank	Feb 8, 2020	Learning-To-RankRetrieval	—Unverified	0
JPLink: On Linking Jobs to Vocational Interest Types	Feb 6, 2020	Learning-To-Rank	—Unverified	0
Boosting API Recommendation with Implicit Feedback	Feb 4, 2020	Active LearningLearning-To-Rank	—Unverified	0
Safe Exploration for Optimizing Contextual Bandits	Feb 2, 2020	counterfactualInformation Retrieval	CodeCode Available	0
Correcting for Selection Bias in Learning-to-rank Systems	Jan 29, 2020	counterfactualLearning-To-Rank	—Unverified	0
Selective Weak Supervision for Neural Information Retrieval	Jan 28, 2020	Information RetrievalLearning-To-Rank	CodeCode Available	1
TopRank+: A Refinement of TopRank Algorithm	Jan 21, 2020	Learning-To-Rank	—Unverified	0
Listwise Learning to Rank by Exploring Unique Ratings	Jan 7, 2020	Learning-To-Rank	CodeCode Available	1
Influence Diagram Bandits	Jan 1, 2020	Learning-To-RankPosition	—Unverified	0
Cost-Sensitive Feature-Value Acquisition Using Feature Relevance	Dec 17, 2019	Learning-To-RankPrediction	—Unverified	0

Show:10 25 50

← PrevPage 44 of 76Next →

No leaderboard results yet.