{"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/learning-logistic-circuits","title":"Learning Logistic Circuits","arxiv_id":"1902.10798","date":"2019-02-27","proceeding":null,"authors":["Yitao Liang","Guy Van Den Broeck"],"abstract":"This paper proposes a new classification model called logistic circuits. On\nMNIST and Fashion datasets, our learning algorithm outperforms neural networks\nthat have an order of magnitude more parameters. Yet, logistic circuits have a\ndistinct origin in symbolic AI, forming a discriminative counterpart to\nprobabilistic-logical circuits such as ACs, SPNs, and PSDDs. We show that\nparameter learning for logistic circuits is convex optimization, and that a\nsimple local search algorithm can induce strong model structures from data.","url_abs":"http://arxiv.org/abs/1902.10798v1","url_pdf":"http://arxiv.org/pdf/1902.10798v1.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":"learning-logistic-circuits","repo_url":"https://github.com/UCLA-StarAI/LogisticCircuit","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1902.10798","atlas_url":"https://app.syntology.ai/?focus=1902.10798","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}