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 471–480 of 753 papers

Title	Date	Tasks	Status
AIBench: An Industry Standard Internet Service AI Benchmark Suite	Aug 13, 2019	BenchmarkingLearning-To-Rank	—Unverified
Influence of Neighborhood on the Preference of an Item in eCommerce Search	Aug 10, 2019	Learning-To-Rank	—Unverified
FAIRY: A Framework for Understanding Relationships between Users' Actions and their Social Feeds	Aug 8, 2019	Learning-To-Rank	CodeCode Available
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation	Jul 30, 2019	Decision MakingLearning-To-Rank	CodeCode Available
Mend The Learning Approach, Not the Data: Insights for Ranking E-Commerce Products	Jul 24, 2019	counterfactualLearning-To-Rank	CodeCode Available
Differentially Private Link Prediction With Protected Connections	Jul 20, 2019	Learning-To-RankLink Prediction	—Unverified
Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval	Jul 19, 2019	Learning-To-RankRetrieval	—Unverified
Unbiased Learning to Rank: Counterfactual and Online Approaches	Jul 16, 2019	counterfactualLearning-To-Rank	—Unverified
To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions	Jul 15, 2019	Benchmarkingcounterfactual	CodeCode Available
pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework	Jul 5, 2019	Deep Learningde novo peptide sequencing	—Unverified

Show:10 25 50

← PrevPage 48 of 76Next →

No leaderboard results yet.