Ontology-enhanced zero-shot learning
Web27 de jun. de 2024 · We hypothesize that ontology axioms will help to improve the quality of predictions and allow us to predict functional annotations for ontology terms without training samples (zero-shot) using only the ontology axioms, thereby combining neural and symbolic AI methods within a single model (Mira et al., 2003).
Ontology-enhanced zero-shot learning
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WebZero-shot Learning (ZSL), which aims to predict for those classes that have never appeared in the training data, has arisen hot research interests. The key of implementing ZSL is to leverage the prior knowledge of classes which builds the semantic relationship between classes and enables the transfer of the learned models (e.g., features) from … WebHá 2 dias · Download Citation On Apr 12, 2024, Xuechen Zhao and others published Feature Enhanced Zero-Shot Stance Detection via Contrastive Learning Find, read and cite all the research you need on ...
WebFew-shot Learning (FSL) is aimed to make predictions based on a limited number of samples. Structured data such as knowledge graphs and ontology libraries has been … Web7 de out. de 2024 · Zero-shot learning (ZSL) has recently attracted more attention in image and text classification areas. Inspired by the humans’ abilities to recognize new objects only from their semantic descriptions and previous recognition experience, ZSL models should be trained using the data of seen classes and recognize unseen classes via their class …
Web1 de abr. de 2024 · Authors: Yuxia Geng (Zhejiang University), Jiaoyan Chen (University of Oxford), Zhuo Chen (Zhejiang University), Jeff Z. Pan (University of Edinburgh), Zhiqu... WebAuthors: Yuxia Geng (Zhejiang University), Jiaoyan Chen (University of Oxford), Zhuo Chen (Zhejiang University), Jeff Z. Pan (University of Edinburgh), Zhiqu...
WebFeature Generating Networks for Zero-Shot Learning. In CVPR. 5542--5551. Google Scholar; Wenjia Xu, Yongqin Xian, Jiuniu Wang, Bernt Schiele, and Zeynep Akata. 2024. …
Web8 de jun. de 2024 · Zero-shot Learning (ZSL), which enables models to predict new classes that have no training samples (i.e., unseen classes), has attracted a lot of research interests in many machine learning tasks, such as image classification (Xian et al., 2024; Frome et al., 2013), relation extraction (Li et al., 2024) and Knowledge Graph (KG) … church tomato seedsWeb26 de fev. de 2024 · OntoZSL: Ontology-enhanced zero-shot learning. In The Web Conference (WWW), 2024. [Gesese et al., 2024] Genet Asefa Gesese, Russa Biswas, Mehwish Alam, and Harald Sack. dexter season 7 dvdWeb15 de fev. de 2024 · Zero-shot Learning (ZSL), which aims to predict for those classes that have never appeared in the training data, has arisen hot research interests. The key of implementing ZSL is to leverage the prior knowledge of classes which builds the semantic relationship between classes and enables the transfer of the learned models (e.g., … dexter season 6 plotWebZero-shot Learning, Ontology, Generative Adversarial Networks, Image Classification, Knowledge Graph Completion ACM Reference Format: Yuxia Geng, Jiaoyan Chen, … church tomah wiWebZero-shot Learning (ZSL), which aims to predict for those classes that have never appeared in the training data, has arisen hot research interests. The key of implementing … church tomatoWeb19 de mar. de 2024 · It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain shift, where the true and learned data distributions for the unseen classes do not match. Although transductive ZSL (TZSL) attempts to improve this by allowing the use of unlabelled examples from the unseen classes, there is still a high … church tomorrow clipartWebOntology learning (ontology extraction, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including extracting the … dexter season 7 synopsis