{"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/systematic-weight-pruning-of-dnns-using","title":"Systematic Weight Pruning of DNNs using Alternating Direction Method of Multipliers","arxiv_id":"1802.05747","date":"2018-02-15","proceeding":null,"authors":["Tianyun Zhang","Shaokai Ye","Yi-Peng Zhang","Yanzhi Wang","Makan Fardad"],"abstract":"We present a systematic weight pruning framework of deep neural networks\n(DNNs) using the alternating direction method of multipliers (ADMM). We first\nformulate the weight pruning problem of DNNs as a constrained nonconvex\noptimization problem, and then adopt the ADMM framework for systematic weight\npruning. We show that ADMM is highly suitable for weight pruning due to the\ncomputational efficiency it offers. We achieve a much higher compression ratio\ncompared with prior work while maintaining the same test accuracy, together\nwith a faster convergence rate. Our models are released at\nhttps://github.com/KaiqiZhang/admm-pruning","url_abs":"http://arxiv.org/abs/1802.05747v2","url_pdf":"http://arxiv.org/pdf/1802.05747v2.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":"systematic-weight-pruning-of-dnns-using","repo_url":"https://github.com/KaiqiZhang/admm-pruning","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"}],"methods":[{"method_slug":"admm","method_name":"ADMM"},{"method_slug":"pruning","method_name":"Pruning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1802.05747","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}