learning to rank

Probabilistic n-Choose-k Models for Classification and Ranking NeurIPS 2012 Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity NeurIPS 2011 Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Functions on Graphs JMLR 2011 A New Probabilistic Model for Rank Aggregation NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Learning to Rank by Optimizing NDCG Measure NeurIPS 2009 Polynomial Semantic Indexing NeurIPS 2009 Ranking Measures and Loss Functions in Learning to Rank NeurIPS 2009 Global Ranking Using Continuous Conditional Random Fields NeurIPS 2008 Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking NeurIPS 2008 Structured ranking learning using cumulative distribution networks NeurIPS 2008 A General Boosting Method and its Application to Learning Ranking Functions for Web Search NeurIPS 2007 COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking NeurIPS 2007 McRank: Learning to Rank Using Multiple Classification and Gradient Boosting NeurIPS 2007 Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006 Learning to Rank with Nonsmooth Cost Functions NeurIPS 2006 An Efficient Boosting Algorithm for Combining Preferences JMLR 2003