{"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/restricted-boltzmann-machines-introduction","title":"Restricted Boltzmann Machines: Introduction and Review","arxiv_id":"1806.07066","date":"2018-06-19","proceeding":null,"authors":["Guido Montufar"],"abstract":"The restricted Boltzmann machine is a network of stochastic units with\nundirected interactions between pairs of visible and hidden units. This model\nwas popularized as a building block of deep learning architectures and has\ncontinued to play an important role in applied and theoretical machine\nlearning. Restricted Boltzmann machines carry a rich structure, with\nconnections to geometry, applied algebra, probability, statistics, machine\nlearning, and other areas. The analysis of these models is attractive in its\nown right and also as a platform to combine and generalize mathematical tools\nfor graphical models with hidden variables. This article gives an introduction\nto the mathematical analysis of restricted Boltzmann machines, reviews recent\nresults on the geometry of the sets of probability distributions representable\nby these models, and suggests a few directions for further investigation.","url_abs":"http://arxiv.org/abs/1806.07066v1","url_pdf":"http://arxiv.org/pdf/1806.07066v1.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":"restricted-boltzmann-machines-introduction","repo_url":"https://github.com/Kevin-Sean-Chen/Restriced_Boltzmann_Machine","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[{"method_slug":"restricted-boltzmann-machine","method_name":"Restricted Boltzmann Machine"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1806.07066","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}