{"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/deep-unsupervised-clustering-using-mixture-of","title":"Deep Unsupervised Clustering Using Mixture of Autoencoders","arxiv_id":"1712.07788","date":"2017-12-21","proceeding":null,"authors":["Dejiao Zhang","Yifan Sun","Brian Eriksson","Laura Balzano"],"abstract":"Unsupervised clustering is one of the most fundamental challenges in machine\nlearning. A popular hypothesis is that data are generated from a union of\nlow-dimensional nonlinear manifolds; thus an approach to clustering is\nidentifying and separating these manifolds. In this paper, we present a novel\napproach to solve this problem by using a mixture of autoencoders. Our model\nconsists of two parts: 1) a collection of autoencoders where each autoencoder\nlearns the underlying manifold of a group of similar objects, and 2) a mixture\nassignment neural network, which takes the concatenated latent vectors from the\nautoencoders as input and infers the distribution over clusters. By jointly\noptimizing the two parts, we simultaneously assign data to clusters and learn\nthe underlying manifolds of each cluster.","url_abs":"http://arxiv.org/abs/1712.07788v2","url_pdf":"http://arxiv.org/pdf/1712.07788v2.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":"deep-unsupervised-clustering-using-mixture-of","repo_url":"https://github.com/icannos/mixture-autoencoder","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1712.07788","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}