Results 21 to 30 of about 3,113,449 (308)
Fast Multi-label Learning [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Embedding approaches have become one of the most pervasive techniques for multi-label classification. However, the training process of embedding methods usually involves a complex quadratic or semidefinite programming problem, or the model may even involve an NP-hard problem. Thus, such methods are prohibitive on large-scale applications.
Xiuwen Gong +2 more
openaire +4 more sources
Multi-label classification using ensembles of pruned sets [PDF]
, 2008 This paper presents a Pruned Sets method (PS) for multi-label classification. It is centred on the concept of treating sets of labels as single labels. This allows the classification process to inherently take into account correlations between labels. By
Pfahringer, Bernhard +5 more
core +1 more source
Applied Sciences, 2023 Multilabel classification of Arabic text is an important task for understanding and analyzing social media content. It can enable the categorization and monitoring of social media posts, the detection of important events, the identification of trending ...
Samah M. Alzanin +3 more
doaj +1 more source
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Multi-label learning aims at assigning a set of appropriate labels to multi-label samples. Although it has been successfully applied in various domains in recent years, most multi-label learning methods require sufficient labeled training samples, because of the large number of possible label sets.
Yuying Xing +4 more
openaire +1 more source
A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection [PDF]
, 2015 This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Multi-Label Correlation-based Feature Selection (LexGA-ML-CFS), which is an extension of the previous single-objective Genetic Algorithm for Multi-label Correlation-based ...
Suwimol Jungjit +3 more
core +1 more source
Simpler is better: a novel genetic algorithm to induce compact multi-label chain classifiers [PDF]
, 2015 Multi-label classification (MLC) is the task of assigning multiple class labels to an object based on the features that describe the object. One of the most effective MLC methods is known as Classifier Chains (CC).
Plastino, Alexandre +5 more
core +1 more source
Multi-Label Knowledge Distillation
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Existing knowledge distillation methods typically work by imparting the knowledge of output logits or intermediate feature maps from the teacher network to the student network, which is very successful in multi-class single-label learning. However, these methods can hardly be extended to the multi-label learning scenario, where each instance is ...
Penghui Yang 0001 +6 more
openaire +4 more sources
Compact learning for multi-label classification [PDF]
Pattern Recognition, 2021 Multi-label classification (MLC) studies the problem where each instance is associated with multiple relevant labels, which leads to the exponential growth of output space. MLC encourages a popular framework named label compression (LC) for capturing label dependency with dimension reduction.
Jiaqi Lv +5 more
openaire +3 more sources
A hierarchical multi-label classification ant colony algorithm for protein function prediction [PDF]
, 2010 This paper proposes a novel ant colony optimisation (ACO) algorithm tailored for the hierarchical multi-label classification problem of protein function prediction.
Otero, Fernando E.B. +5 more
core +1 more source
EnzML : multi-label prediction of enzyme classes using InterPro signatures [PDF]
, 2012 LDF is funded by ONDEX DTG, BBSRC TPS Grant BB/F529038/1 of the Centre for Systems Biology at Edinburgh and the University of Newcastle. SA is supported by by a Wellcome Trust Value In People award and, together with IG, the Centre for Systems Biology at
Goryanin Igor +14 more
core +1 more source