{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/evidence-transfer-for-improving-clustering","title":"Evidence Transfer for Improving Clustering Tasks Using External Categorical Evidence","arxiv_id":"1811.03909","date":"2018-11-09","proceeding":null,"authors":["Athanasios Davvetas","Iraklis A. Klampanos","Vangelis Karkaletsis"],"abstract":"In this paper we introduce evidence transfer for clustering, a deep learning\nmethod that can incrementally manipulate the latent representations of an\nautoencoder, according to external categorical evidence, in order to improve a\nclustering outcome. By evidence transfer we define the process by which the\ncategorical outcome of an external, auxiliary task is exploited to improve a\nprimary task, in this case representation learning for clustering. Our proposed\nmethod makes no assumptions regarding the categorical evidence presented, nor\nthe structure of the latent space. We compare our method, against the baseline\nsolution by performing k-means clustering before and after its deployment.\nExperiments with three different kinds of evidence show that our method\neffectively manipulates the latent representations when introduced with real\ncorresponding evidence, while remaining robust when presented with low quality\nevidence.","url_abs":"http://arxiv.org/abs/1811.03909v2","url_pdf":"http://arxiv.org/pdf/1811.03909v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"evidence-transfer-for-improving-clustering","repo_url":"https://github.com/davidath/evitrac","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[{"method_slug":"k-means-clustering","method_name":"k-Means Clustering"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}