Results 1 to 10 of about 1,099,722 (325)
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
Unbiased Learning to Rank with Unbiased Propensity Estimation [PDF]
, 2018 Learning to rank with biased click data is a well-known challenge. A variety of methods has been explored to debias click data for learning to rank such as click models, result interleaving and, more recently, the unbiased learning-to-rank framework ...
Qingyao Ai +4 more
openalex +3 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
Differentiable Unbiased Online Learning to Rank [PDF]
, 2018 Online Learning to Rank (OLTR) methods optimize rankers based on user interactions. State-of-the-art OLTR methods are built specifically for linear models. Their approaches do not extend well to non-linear models such as neural networks.
Harrie Oosterhuis, Maarten de Rijke
openalex +3 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
pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework. [PDF]
Bioinformatics, 2019 Yang H, Chi H, Zeng WF, Zhou WJ, He SM.
europepmc +3 more sources
PeerRank: Robust Learning to Rank With Peer Loss Over Noisy Labels
IEEE Access, 2022 User-generated data are extensively utilized in learning to rank as they are easy to collect and up-to-date. However, the data inevitably contain noisy labels attributed to users’ annotation mistakes, lack of domain knowledge, system failure, etc.,
Xin Wu, Qing Liu, Jiarui Qin, Yong Yu
doaj +1 more source
Differentiable Ranking Metric Using Relaxed Sorting for Top-K Recommendation
IEEE Access, 2021 Most recommenders generate recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top- $K$ -items of high scores.
Hyunsung Lee +4 more
doaj +1 more source