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 341–350 of 753 papers

Title	Date	Tasks	Status
Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality	Jul 29, 2021	Learning-To-RankRecommendation Systems	—Unverified
Ranker-agnostic Contextual Position Bias Estimation	Jul 28, 2021	Learning-To-RankPosition	—Unverified
RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank	Jul 20, 2021	Image Super-ResolutionLearning-To-Rank	—Unverified
Leveraging semantically similar queries for ranking via combining representations	Jun 23, 2021	Learning-To-Rank	—Unverified
Learning to Rank Question Answer Pairs with Bilateral Contrastive Data Augmentation	Jun 21, 2021	Answer GenerationData Augmentation	—Unverified
RankDetNet: Delving Into Ranking Constraints for Object Detection	Jun 19, 2021	3D Object DetectionClassification	—Unverified
Learning to Rank Words: Optimizing Ranking Metrics for Word Spotting	Jun 9, 2021	Learning-To-RankRetrieval	CodeCode Available
On Learning to Rank Long Sequences with Contextual Bandits	Jun 7, 2021	Learning-To-RankMulti-Armed Bandits	—Unverified
New Insights into Metric Optimization for Ranking-based Recommendation	Jun 4, 2021	Learning-To-RankRecommendation Systems	CodeCode Available
Zipf Matrix Factorization : Matrix Factorization with Matthew Effect Reduction	Jun 1, 2021	FairnessLearning-To-Rank	CodeCode Available

Show:10 25 50

← PrevPage 35 of 76Next →

No leaderboard results yet.