Results 11 to 20 of about 954,983 (314)
Annals of Mathematics and Artificial Intelligence, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fietzke, A. +1 more
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Vertex Graceful Labeling-Some Path Related Graphs [PDF]
, 2013 Treating subjects as vertex graceful graphs, vertex graceful labeling, caterpillar, actinia graphs, Smarandachely vertex m ...
Balaganesan, P. +2 more
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Multi-Label Classification with Label Clusters
Knowledge and Information Systems, 2023 Abstract Multi-Label Classification is the task of simultaneously predicting a set of labels for an instance. Typically, two approaches are used: global, which trains a single classifier to deal with all classes at once, and local, which divides the problem into many binary problems.
Elaine Cecília Gatto +2 more
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The role of exercise and diet in maintaining bone health
Journal of Physical Fitness and Sports Medicine, 2012 Prevention is the most important measure against osteoporosis, since bone mass, once it is lost, cannot be recovered. Bone mass, in both men and women, reaches a maximum level in the 20s to 30s age range, and maintains this level or slightly increases ...
Yoshiko Ishimi, Kaoru Yanaka
doaj +1 more source
Point labeling with sliding labels
Computational Geometry, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
van Kreveld, M.J. +2 more
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Super Mean Labeling of Some Classes of Graphs [PDF]
, 2012 Approaching topics as Smarandachely super m-mean labeling, Smarandachely super m-mean graph, super mean labeling, super mean ...
P.Jeyanthi +3 more
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LABEL PROPAGATION FOR LEARNING WITH LABEL PROPORTIONS [PDF]
2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), 2018 Accepted to MLSP ...
Rafael Poyiadzi +2 more
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Super Fibonacci Graceful Labeling [PDF]
, 2011 Approaching topics such as Smarandache-Fibonacci triple, graceful labeling, Fibonacci graceful labeling, super Smarandache-Fibonacci graceful graph, super Fibonacci graceful ...
Sridevi, R. +2 more
core +1 more source
Translational Oncology, 2019 Off-target activities of drug candidates observed during in vitro pharmacological profiling frequently do not translate to adverse events (AEs) in human. This could be because off-target activities do not have functional consequences, are not observed at
Hamid R. Amouzadeh +6 more
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Multi-label Learning with Label Enhancement [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 The task of multi-label learning is to predict a set of relevant labels for the unseen instance. Traditional multi-label learning algorithms treat each class label as a logical indicator of whether the corresponding label is relevant or irrelevant to the instance, i.e., +1 represents relevant to the instance and -1 represents irrelevant to the instance.
Ruifeng Shao +2 more
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