{"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/distributed-convolutional-dictionary-learning","title":"Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals","arxiv_id":"1901.09235","date":"2019-01-26","proceeding":null,"authors":["Thomas Moreau","Alexandre Gramfort"],"abstract":"Convolutional dictionary learning (CDL) estimates shift invariant basis\nadapted to multidimensional data. CDL has proven useful for image denoising or\ninpainting, as well as for pattern discovery on multivariate signals. As\nestimated patterns can be positioned anywhere in signals or images,\noptimization techniques face the difficulty of working in extremely high\ndimensions with millions of pixels or time samples, contrarily to standard\npatch-based dictionary learning. To address this optimization problem, this\nwork proposes a distributed and asynchronous algorithm, employing locally\ngreedy coordinate descent and an asynchronous locking mechanism that does not\nrequire a central server. This algorithm can be used to distribute the\ncomputation on a number of workers which scales linearly with the encoded\nsignal's size. Experiments confirm the scaling properties which allows us to\nlearn patterns on large scales images from the Hubble Space Telescope.","url_abs":"http://arxiv.org/abs/1901.09235v1","url_pdf":"http://arxiv.org/pdf/1901.09235v1.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":"distributed-convolutional-dictionary-learning","repo_url":"https://github.com/tommoral/dicodile","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"},{"task_slug":"dictionary-learning","task_name":"Dictionary Learning"},{"task_slug":"image-denoising","task_name":"Image Denoising"}],"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}