Results 11 to 20 of about 1,099,722 (325)
Learning to rank using privileged information [PDF]
2013 IEEE International Conference on Computer Vision, 2013 Many computer vision problems have an asymmetric distribution of information between training and test time. In this work, we study the case where we are given additional information about the training data, which however will not be available at test ...
Lampert, Christoph H +2 more
core +6 more sources
Deep Multi-view Learning to Rank [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2019 We study the problem of learning to rank from multiple information sources. Though multi-view learning and learning to rank have been studied extensively leading to a wide range of applications, multi-view learning to rank as a synergy of both topics has
Cao, Guanqun +4 more
core +3 more sources
Answering questions by learning to rank -- Learning to rank by answering questions [PDF]
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019 Presented at EMNLP 2019; 10 pages, 5 ...
George-Sebastian Pîrtoacă +2 more
openalex +4 more sources
RankEval: Evaluation and investigation of ranking models
SoftwareX, 2020 RankEval is a Python open-source tool for the analysis and evaluation of ranking models based on ensembles of decision trees. Learning-to-Rank (LtR) approaches that generate tree-ensembles are considered the most effective solution for difficult ranking ...
Claudio Lucchese +4 more
doaj +1 more source
Learning to rank spatio-temporal event hotspots
Crime Science, 2020 Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk ...
George Mohler +3 more
doaj +1 more source
Effective Learning to Rank Persian Web Content [PDF]
Journal of Information Technology Management, 2019 Persian language is one of the most widely used languages in the Web environment. Hence, the Persian Web includes invaluable information that is required to be retrieved effectively.
Amir Hosein Keyhanipour
doaj +1 more source
Fair pairwise learning to rank [PDF]
2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020 Ranking algorithms based on Neural Networks have been a topic of recent research. Ranking is employed in everyday applications like product recommendations, search results, or even in finding good candidates for hiring. However, Neural Networks are mostly opaque tools, and it is hard to evaluate why a specific candidate, for instance, was not ...
Mattia Cerrato +4 more
openaire +2 more sources
Journal of King Saud University: Computer and Information Sciences, 2020 This paper proposed a new method for learning to rank documents using enumerative feature subsetting in the presence of the implicit user feedback of the various classes of users.
Mohd Wazih Ahmad +2 more
doaj +1 more source
Learning-to-rank vs ranking-to-learn
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 2020 In Continuous Integration (CI), regression testing is constrained by the time between commits. This demands for careful selection and/or prioritization of test cases within test suites too large to be run entirely. To this aim, some Machine Learning (ML) techniques have been proposed, as an alternative to deterministic approaches.
Antonia Bertolino +4 more
openaire +2 more sources
Boosting the Learning for Ranking Patterns
Algorithms, 2023 Pattern mining is a valuable tool for exploratory data analysis, but identifying relevant patterns for a specific user is challenging. Various interestingness measures have been developed to evaluate patterns, but they may not efficiently estimate user ...
Nassim Belmecheri +4 more
doaj +1 more source