{"id":20620616,"url":"https://github.com/lcav/sketchrls","last_synced_at":"2026-03-09T08:32:58.412Z","repository":{"id":146199739,"uuid":"50099931","full_name":"LCAV/sketchrls","owner":"LCAV","description":"Sketch RLS is an adaptive filtering algorithm that brings sketching ideas into the classical recursive least squares algorithm. This is the python implementation of the algorithm.","archived":false,"fork":false,"pushed_at":"2016-01-21T10:36:34.000Z","size":5061,"stargazers_count":8,"open_issues_count":1,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-15T12:18:03.778Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LCAV.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-01-21T10:24:47.000Z","updated_at":"2025-01-20T10:46:49.000Z","dependencies_parsed_at":"2023-04-18T14:25:13.333Z","dependency_job_id":null,"html_url":"https://github.com/LCAV/sketchrls","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/LCAV/sketchrls","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsketchrls","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsketchrls/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsketchrls/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsketchrls/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LCAV","download_url":"https://codeload.github.com/LCAV/sketchrls/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LCAV%2Fsketchrls/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30287845,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-09T02:57:19.223Z","status":"ssl_error","status_checked_at":"2026-03-09T02:56:26.373Z","response_time":61,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-16T12:14:59.272Z","updated_at":"2026-03-09T08:32:58.387Z","avatar_url":"https://github.com/LCAV.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"The Recursive Hessian Sketch for Adaptive Filtering\n===================================================\n\nThis is the companion code that was used to produce the figures\nof the paper __The Recursive Hessian Sketch for Adaptive Filtering__\nby Robin Scheibler and Martin Vetterli, submitted to ICASSP 2016.\n\nAuthors\n-------\n\nRobin Scheibler, and Martin Vetterli are with \nLaboratory for Audiovisual Communications ([LCAV](http://lcav.epfl.ch)) at \n[EPFL](http://www.epfl.ch).\n\n\u003cimg src=\"http://lcav.epfl.ch/files/content/sites/lcav/files/images/Home/LCAV_anim_200.gif\"\u003e\n\n#### Contact\n\n[Robin Scheibler](mailto:ivan[dot]dokmanic[at]epfl[dot]ch) \u003cbr\u003e\nEPFL-IC-LCAV \u003cbr\u003e\nBC Building \u003cbr\u003e\nStation 14 \u003cbr\u003e\n1015 Lausanne\n\nRun the code\n------------\n\nAll the code is pure python and uses only numpy, scipy, matplotlib. The code was\nrun with ipython.\n\n    $ ipython --version\n    3.2.1\n\nWe use anaconda to install python, numpy, matplotlib, etc.\n\n### Code organization\n\nAll the classical adaptive filters are implemented in `adaptive_filters.py`.\n\nThe proposed algorithm is in `sketch_rls.py`.\n\n### Figures 2. \n\nSimply run\n\n    $ ipython ./figure_Complexity.py\n\n### Figures 3.\n\nStart an ipython cluster in the repository.\n\n    $ ipcluster start -n x\n\nwhere `x` is the number of engines you want to use. You can change the number\nof loops directly in the script line 42. Then, run the command\n\n    $ ipython figure_MSE_sim.py\n\nThis will run the long simulation needed. The result will be stored\nin the folder `sim_data` and the name of the file will contain the date and time.\n\nCopy the date and time in the file `figure_MSE_plot.py` line 61-64. Then run\n\n    $ ipython figure_MSE_plot.py\n\nFinally, the file `figure_MSE_test.py` allows to be quickly edited to test\ndifferent parameters.\n\n    $ ipython figure_MSE_test.py\n\nLicense\n-------\n\nCopyright (c) 2016, LCAV\n\nThis code is free to reuse for non-commercial purpose such as academic or\neducational. For any other use, please contact the authors.\n\n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"\u003e\n\u003cimg alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png\" /\u003e\n\u003c/a\u003e\u003cbr/\u003e\n\u003cspan xmlns:dct=\"http://purl.org/dc/terms/\" property=\"dct:title\"\u003eSketch RLS\u003c/span\u003e \nby \u003ca xmlns:cc=\"http://creativecommons.org/ns#\" href=\"http://lcav.epfl.ch\" property=\"cc:attributionName\" rel=\"cc:attributionURL\"\u003eLCAV, EPFL\u003c/a\u003e \nis licensed under a \n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"\u003eCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License\u003c/a\u003e.\u003cbr /\u003e\nBased on a work at \u003ca xmlns:dct=\"http://purl.org/dc/terms/\" href=\"https://github.com/LCAV/sketchrls\" rel=\"dct:source\"\u003ehttps://github.com/LCAV/sketchrls\u003c/a\u003e.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcav%2Fsketchrls","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flcav%2Fsketchrls","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcav%2Fsketchrls/lists"}