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

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Showing 26–50 of 753 papers

Title	Date	Tasks	Status	Hype
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank	Apr 25, 2023	Learning-To-Rank	CodeCode Available	1
Lero: A Learning-to-Rank Query Optimizer	Feb 14, 2023	Binary ClassificationLearning-To-Rank	CodeCode Available	1
RankDNN: Learning to Rank for Few-shot Learning	Nov 28, 2022	Few-Shot Learningimage-classification	CodeCode Available	1
RankCSE: Unsupervised Representation Learning via Learning to Rank	Nov 14, 2022	Contrastive LearningLearning-To-Rank	CodeCode Available	1
Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimization	Oct 4, 2022	Contrastive LearningImage Retrieval	CodeCode Available	1
A Large Scale Search Dataset for Unbiased Learning to Rank	Jul 7, 2022	Causal DiscoveryLanguage Modelling	CodeCode Available	1
ILMART: Interpretable Ranking with Constrained LambdaMART	Jun 1, 2022	Learning-To-Rank	CodeCode Available	1
Learning-to-Rank at the Speed of Sampling: Plackett-Luce Gradient Estimation With Minimal Computational Complexity	Apr 22, 2022	Learning-To-Rank	CodeCode Available	1
Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression	Apr 1, 2022	Head Pose EstimationLearning-To-Rank	CodeCode Available	1
Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference	Feb 12, 2022	Entity TypingLearning-To-Rank	CodeCode Available	1
Decision-Focused Learning: Through the Lens of Learning to Rank	Dec 7, 2021	Combinatorial OptimizationDecision Making	CodeCode Available	1
Pairwise Learning for Neural Link Prediction	Dec 6, 2021	Learning-To-RankLink Prediction	CodeCode Available	1
An Efficient Approach for Cross-Silo Federated Learning to Rank	Jun 21, 2021	Federated LearningLearning-To-Rank	CodeCode Available	1
Enhancing Cross-Sectional Currency Strategies by Context-Aware Learning to Rank with Self-Attention	May 20, 2021	Information RetrievalLearning-To-Rank	CodeCode Available	1
SmoothI: Smooth Rank Indicators for Differentiable IR Metrics	May 3, 2021	Information RetrievalLearning-To-Rank	CodeCode Available	1
Learning to Rank Microphones for Distant Speech Recognition	Apr 6, 2021	channel selectionDecoder	CodeCode Available	1
NeuralNDCG: Direct Optimisation of a Ranking Metric via Differentiable Relaxation of Sorting	Feb 15, 2021	Information RetrievalLearning-To-Rank	CodeCode Available	1
On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance	Feb 1, 2021	Learning-To-RankRecommendation Systems	CodeCode Available	1
On the Calibration and Uncertainty of Neural Learning to Rank Models	Jan 12, 2021	Document RankingLearning-To-Rank	CodeCode Available	1
Weakly Supervised Label Smoothing	Dec 15, 2020	Learning-To-RankPassage Retrieval	CodeCode Available	1
PiRank: Scalable Learning To Rank via Differentiable Sorting	Dec 12, 2020	Learning-To-Rank	CodeCode Available	1
Unifying Online and Counterfactual Learning to Rank	Dec 8, 2020	counterfactualLearning-To-Rank	CodeCode Available	1
PT-Ranking: A Benchmarking Platform for Neural Learning-to-Rank	Aug 31, 2020	BenchmarkingLearning-To-Rank	CodeCode Available	1
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems	Aug 19, 2020	Click-Through Rate PredictionLearning-To-Rank	CodeCode Available	1
SERank: Optimize Sequencewise Learning to Rank Using Squeeze-and-Excitation Network	Jun 7, 2020	Learning-To-RankQuestion Answering	CodeCode Available	1

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