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 701–710 of 753 papers

Title	Date	Tasks	Status
Detect2Rank : Combining Object Detectors Using Learning to Rank	Dec 26, 2014	Learning-To-RankObject	—Unverified
Ranking via Robust Binary Classification	Dec 1, 2014	Binary ClassificationClassification	—Unverified
A Representation Theory for Ranking Functions	Dec 1, 2014	Learning-To-RankReranking	—Unverified
Learning to Rank Binary Codes	Oct 21, 2014	BinarizationImage Retrieval	—Unverified
Multivariate Spearman's rho for aggregating ranks using copulas	Oct 16, 2014	Learning-To-Rank	—Unverified
Learning to Differentiate Better from Worse Translations	Oct 1, 2014	Learning-To-RankMachine Translation	—Unverified
Invited Talk: Learning from Rational Behavior	Oct 1, 2014	Decision MakingLearning-To-Rank	—Unverified
Fitting Sentence Level Translation Evaluation with Many Dense Features	Oct 1, 2014	Learning-To-RankMachine Translation	CodeCode Available
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking	Aug 9, 2014	ClusteringInformation Retrieval	—Unverified
Learning the Peculiar Value of Actions	Aug 1, 2014	Learning-To-Rank	—Unverified

Show:10 25 50

← PrevPage 71 of 76Next →

No leaderboard results yet.