conftrace_

learning to rank

185 papers

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Also known as

LTR LETOR

Co-occurring keywords

information retrieval (1514) online learning (1777) regret bound (1926) neural network (6616) question answering (2963) document ranking (74) multi-armed bandit (1098) preference learning (418) listwise ranking (31) rank aggregation (53)

Papers

Activity Auto-Completion: Predicting Human Activities From Partial Videos ICCV 2015
Learning Efficient Anomaly Detectors from K-NN Graphs AISTATS 2015
Generalization error bounds for learning to rank: Does the length of document lists matter? ICML 2015
Online Ranking with Top-1 Feedback AISTATS 2015
Predtron: A Family of Online Algorithms for General Prediction Problems NIPS 2015
Quality Assessment for Comparing Image Enhancement Algorithms CVPR 2014
Active Learning Using Smooth Relative Regret Approximations with Applications JMLR 2014
New Learning Methods for Supervised and Unsupervised Preference Aggregation JMLR 2014
Ranking via Robust Binary Classification NIPS 2014
A Learning-to-Rank Approach for Image Color Enhancement CVPR 2014
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections JMLR 2013
A Theoretical Analysis of NDCG Type Ranking Measures COLT 2013
Implied Feedback: Learning Nuances of User Behavior in Image Search ICCV 2013
Learning to Rank Using Privileged Information ICCV 2013
On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NIPS 2012
An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity JMLR 2012
Active Learning Using Smooth Relative Regret Approximations with Applications COLT 2012
Probabilistic n-Choose-k Models for Classification and Ranking NIPS 2012
Accuracy at the Top NIPS 2012
Perturbation based Large Margin Approach for Ranking AISTATS 2012
Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity NIPS 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 NIPS 2010
Two-Layer Generalization Analysis for Ranking Using Rademacher Average NIPS 2010
Ranking Measures and Loss Functions in Learning to Rank NIPS 2009