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pro vyhledávání: '"Vandaele, Robin"'
Unsupervised representation learning methods are widely used for gaining insight into high-dimensional, unstructured, or structured data. In some cases, users may have prior topological knowledge about the data, such as a known cluster structure or t
Externí odkaz:
http://arxiv.org/abs/2301.03338
Unsupervised feature learning often finds low-dimensional embeddings that capture the structure of complex data. For tasks for which prior expert topological knowledge is available, incorporating this into the learned representation may lead to highe
Externí odkaz:
http://arxiv.org/abs/2110.09193
Distances between data points are widely used in machine learning applications. Yet, when corrupted by noise, these distances -- and thus the models based upon them -- may lose their usefulness in high dimensions. Indeed, the small marginal effects o
Externí odkaz:
http://arxiv.org/abs/2109.10569
Autor:
Vandaele, Robin, Mukherjee, Pritam, Selby, Heather Marie, Shah, Rajesh Pravin, Gevaert, Olivier
Publikováno v:
In Patterns 13 January 2023 4(1)
Akademický článek
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Unsupervised representation learning methods are widely used for gaining insight into high-dimensional, unstructured, or structured data. In some cases, users may have prior topological knowledge about the data, such as a known cluster structure or t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c330718172975c821e0362cb99ed3483
http://arxiv.org/abs/2110.09193
http://arxiv.org/abs/2110.09193
Publikováno v:
In Pattern Recognition Letters July 2021 147:85-92
Publikováno v:
JOURNAL OF MACHINE LEARNING RESEARCH
We consider the problem of inferring simplified topological substructures—which we term backbones—in metric and non-metric graphs. Intuitively, these are subgraphs with ‘few’ nodes, multifurcations, and cycles, that model the topology of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______330::03a6720f40d417762c64a4d7706f0cda
https://hdl.handle.net/1854/LU-8678984
https://hdl.handle.net/1854/LU-8678984
Akademický článek
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