Learning to Rank: Regret Lower Bounds and Efficient Algorithms.
Richard CombesStefan MagureanuAlexandre ProutièreCyrille LarochePublished in: SIGMETRICS (2015)
Keyphrases
- learning to rank
- lower bound
- upper bound
- loss function
- ranking functions
- information retrieval
- direct optimization
- np hard
- evaluation measures
- ranking svm
- objective function
- test collection
- evaluation metrics
- document retrieval
- learning to rank algorithms
- optimal solution
- supervised learning
- collaborative filtering
- query dependent
- online algorithms
- ranking models
- machine learning
- optimization problems
- regret bounds
- binary classification
- probabilistic model
- retrieval systems
- pairwise
- online learning