{"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/improved-preconditioner-for-hessian-free","title":"Improved Preconditioner for Hessian Free Optimization","arxiv_id":null,"date":"2010-10-01","proceeding":"NIPS 2010 10","authors":["Olivier Chapelle","Dumitru Erhan"],"abstract":"We investigate the use of Hessian Free optimization for learning deep autoencoders. One of the critical components in that algorithm is the choice\r\nof the preconditioner. We argue in this paper that the Jacobi preconditioner leads to faster optimization and we show how it can be accurately\r\nand efficiently estimated using a randomized algorithm.","url_abs":"http://olivier.chapelle.cc/pub/precond.pdf","url_pdf":"http://olivier.chapelle.cc/pub/precond.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":"improved-preconditioner-for-hessian-free","repo_url":"https://github.com/doomie/HessianFree","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"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}