Query-Level Stability and Generalization in Learning to Rank
A Robust Ranking Methodology based on Diverse Calibration of AdaBoost
Computational advertising: business models, technologies and issues (CoAd)
Optimizing Estimated Loss Reduction for Active Sampling in Rank Learning
Transfer Learning for Item Recommendations and Knowledge Graph Completion in Item Related Domains via A Co-Factorization Model
Combined Regression and Ranking
Diversifying Search Results
Object Ranking
Online Learning
Generalization error bounds for learning to rank: Does the length of document lists matter?