Results 11 to 20 of about 290,195 (301)
k-L(2, 1)-labelling for planar graphs is NP-complete for k>=4 [PDF]
, 2009 A mapping from the vertex set of a graph G=(V,E) into an interval of integers {0,...,k} is an L(2,1)-labelling of G of span k if any two adjacent vertices are mapped onto integers that are at least 2 apart, and every two vertices with a common ...
Havet, F, Eggemann, N, Noble, S D
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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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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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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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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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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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Multi-label Classification with Meta-Labels [PDF]
2014 IEEE International Conference on Data Mining, 2014 The area of multi-label classification has rapidly developed in recent years. It has become widely known that the baseline binary relevance approach can easily be outperformed by methods which learn labels together. A number of methods have grown around the label power set approach, which models label combinations together as class values in a multi ...
Jesse Read, Antti Puurula, Albert Bifet
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Chemosensors, 2022 Five new disubstituted 2,6-thioaryl-BODIPY dyes were synthesized via selective aromatic electrophilic substitution from commercially available thiophenols.
Abigail E. Reese +10 more
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An integrated environmental and fairtrade labelling scheme for product supply chains [PDF]
, 2014 Environmental initiatives such as carbon labelling have been suggested as a driver for achieving sustainable production systems of product supply chains. The paper therefore presents a systematic process of developing an environmental labelling framework
Feng, K. +8 more
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A note on root projection and labelling
Stellenbosch Papers in Linguistics, 2017 This paper identifies a problem with a hypothesis put forward in Chomsky (2013) in relation to his labelling algorithm. Chomsky suggests that category-neutral roots do not qualify as labels and cannot project.
Zeller, Jochen
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