Results 1 to 10 of about 1,093,151 (324)
Learning to rank Higgs boson candidates [PDF]
Scientific Reports, 2022 In the extensive search for new physics, the precise measurement of the Higgs boson continues to play an important role. To this end, machine learning techniques have been recently applied to processes like the Higgs production via vector-boson fusion ...
Marius Köppel +6 more
doaj +6 more sources
Software defect prediction using learning to rank approach [PDF]
Scientific Reports, 2023 Software defect prediction (SDP) plays a significant role in detecting the most likely defective software modules and optimizing the allocation of testing resources. In practice, though, project managers must not only identify defective modules, but also
Ali Bou Nassif +6 more
doaj +2 more sources
Learning to Rank from Medical Imaging Data [PDF]
, 2012 Medical images can be used to predict a clinical score coding for the severity of a disease, a pain level or the complexity of a cognitive task. In all these cases, the predicted variable has a natural order.
Fabián Pedregosa +5 more
openalex +6 more sources
Learning to Rank Reviewers for Pull Requests [PDF]
IEEE Access, 2019 In pull-based software development, anyone who wants to contribute to a project can request integration of the code changes to the public repository by sending a pull request to the development team.
Xin Ye
doaj +2 more sources
Automatic Estimation of Ulcerative Colitis Severity by Learning to Rank With Calibration [PDF]
IEEE Access, 2022 For automatic disease-severity-level estimation, a large-scale medical image dataset with level annotations is generally necessary. However, attaching absolute-level annotations (such as levels 0, 1, and 3) is very costly and even inaccurate due to the ...
Takeaki Kadota +6 more
doaj +2 more sources
Distributionally robust learning-to-rank under the Wasserstein metric. [PDF]
PLoS ONE, 2023 Despite their satisfactory performance, most existing listwise Learning-To-Rank (LTR) models do not consider the crucial issue of robustness. A data set can be contaminated in various ways, including human error in labeling or annotation, distributional ...
Shahabeddin Sotudian +2 more
doaj +3 more sources
Deep Multi-View Learning to Rank [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2021 Published at IEEE ...
Guanqun Cao +4 more
openaire +4 more sources
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 time. This situation is called learning using privileged information (LUPI).
Viktoriia Sharmanska +2 more
openaire +7 more sources
iPiDA-LTR: Identifying piwi-interacting RNA-disease associations based on Learning to Rank. [PDF]
PLoS Computational Biology, 2022 Piwi-interacting RNAs (piRNAs) are regarded as drug targets and biomarkers for the diagnosis and therapy of diseases. However, biological experiments cost substantial time and resources, and the existing computational methods only focus on identifying ...
Wenxiang Zhang, Jialu Hou, Bin Liu
doaj +2 more sources
Learning to rank figures within a biomedical article. [PDF]
PLoS ONE, 2014 Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their ...
Feifan Liu, Hong Yu
doaj +2 more sources