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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 481–490 of 753 papers

Title	Date	Tasks	Status	Hype
Learning to Blindly Assess Image Quality in the Laboratory and Wild	Jul 1, 2019	Image Quality AssessmentLearning-To-Rank	CodeCode Available	1
Learning to Rank Broad and Narrow Queries in E-Commerce	Jul 1, 2019	DenoisingFeature Importance	—Unverified	0
Practical User Feedback-driven Internal Search Using Online Learning to Rank	Jun 15, 2019	ArticlesInformation Retrieval	—Unverified	0
Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks	Jun 14, 2019	Deep AttentionLearning-To-Rank	—Unverified	0
Towards Amortized Ranking-Critical Training for Collaborative Filtering	Jun 10, 2019	Collaborative FilteringLearning-To-Rank	CodeCode Available	1
Variance Reduction in Gradient Exploration for Online Learning to Rank	Jun 10, 2019	Learning-To-Rank	—Unverified	0
Learning to Rank for Plausible Plausibility	Jun 5, 2019	Learning-To-RankNatural Language Understanding	—Unverified	0
A Passage-Based Approach to Learning to Rank Documents	Jun 5, 2019	Document RankingLearning-To-Rank	—Unverified	0
Cross-lingual Subjectivity Detection for Resource Lean Languages	Jun 1, 2019	Language ModelingLanguage Modelling	—Unverified	0
A Study of Latent Structured Prediction Approaches to Passage Reranking	Jun 1, 2019	Learning-To-RankPassage Reranking	—Unverified	0

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