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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Poisoning Knowledge Graph Embeddings via Relation Inference Patterns ... Bhardwaj, Peru; Kelleher, John; Costabello, Luca. - : arXiv, 2021 BASE Show details 2 Language-Driven Region Pointer Advancement for Controllable Image Captioning ... Lindh, Annika; Ross, Robert J.; Kelleher, John D.. - : arXiv, 2020 BASE Show details 3 Semantic Relatedness and Taxonomic Word Embeddings ... Kacmajor, Magdalena; Kelleher, John D.; Klubicka, Filip; Maldonado, Alfredo. - : arXiv, 2020 Abstract: This paper connects a series of papers dealing with taxonomic word embeddings. It begins by noting that there are different types of semantic relatedness and that different lexical representations encode different forms of relatedness. A particularly important distinction within semantic relatedness is that of thematic versus taxonomic relatedness. Next, we present a number of experiments that analyse taxonomic embeddings that have been trained on a synthetic corpus that has been generated via a random walk over a taxonomy. These experiments demonstrate how the properties of the synthetic corpus, such as the percentage of rare words, are affected by the shape of the knowledge graph the corpus is generated from. Finally, we explore the interactions between the relative sizes of natural and synthetic corpora on the performance of embeddings when taxonomic and thematic embeddings are combined. ... : 7 pages 0 figures ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2002.06235 https://arxiv.org/abs/2002.06235 BASE Hide details 4 Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing ... Dobnik, Simon; Kelleher, John D.. - : arXiv, 2018 BASE Show details 5 What is not where: the challenge of integrating spatial representations into deep learning architectures ... Kelleher, John D.; Dobnik, Simon. - : arXiv, 2018 BASE Show details 6 Is it worth it? Budget-related evaluation metrics for model selection ... Klubička, Filip; Salton, Giancarlo D.; Kelleher, John D.. - : arXiv, 2018 BASE Show details

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