{"id":18390587,"url":"https://github.com/airoldilab/sas","last_synced_at":"2026-01-23T04:56:40.574Z","repository":{"id":73415675,"uuid":"15808978","full_name":"airoldilab/SAS","owner":"airoldilab","description":"Sort and Smooth Algorithm for Graphon Estimation (Matlab)","archived":false,"fork":false,"pushed_at":"2014-01-10T20:42:01.000Z","size":2584,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-04-12T09:57:34.318Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Matlab","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/airoldilab.png","metadata":{"files":{"readme":"Readme.txt","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2014-01-10T20:36:47.000Z","updated_at":"2024-11-27T08:17:39.000Z","dependencies_parsed_at":"2023-02-24T00:31:14.584Z","dependency_job_id":null,"html_url":"https://github.com/airoldilab/SAS","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/airoldilab/SAS","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airoldilab%2FSAS","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airoldilab%2FSAS/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airoldilab%2FSAS/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airoldilab%2FSAS/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/airoldilab","download_url":"https://codeload.github.com/airoldilab/SAS/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/airoldilab%2FSAS/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28680623,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-23T04:33:33.518Z","status":"ssl_error","status_checked_at":"2026-01-23T04:33:30.433Z","response_time":59,"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":"2024-11-06T01:48:27.585Z","updated_at":"2026-01-23T04:56:40.560Z","avatar_url":"https://github.com/airoldilab.png","language":"Matlab","funding_links":[],"categories":[],"sub_categories":[],"readme":"================================================\nSort and Smooth (SAS) Algorithm for Consistent Graphon Estimation\n\n\n================================================\nThis MATLAB package is a supplement to the paper \n\nS. H. Chan and E. M. Airoldi, \"A Consistent Histogram Estimator for Exchangeable Graph Models\", in Proceedings of International Conference on Machine Learning, 2014.\n\n\n================================================\nContent:\n\n1. Construct Graphs from a Graphon\n\tMethod 1: [G P u] = construct_a_graph(w,n,T)\n\t\tInput:  w - a Graphon \n\t\t\tn - number of nodes\n\t\t\tT - number of observations\n\t\tOutput: G - graph (size nxnxT)\n\t\t\tP - probability of each node\n\t\t\tu - label indices\n\n\tMethod 2: G = construct_a_graph_from_P(P,n,T)\n\t\tInput:  P - probability of each node\n\t\t\tn - number of nodes\n\t\t\tT - number of observations\n\t\tOutput: G - graph (size nxnxT)\n\n2. Sorting and Smoothing (sort_and_smooth.m)\n\tInput:  G    - a graph\n\tOutput: west - estimated graphon\n\t\n\tAlgorithm dependency: ./deconvtv_v1/\n\n\n3. Results reported in the paper\n\tFigure1.m - plot a twin graphon\n\tFigure2.m - display an example of the SAS algorithm\n\tFigure3.m - results of SAS, USVT and SBA for graphons no. 5 and no. 10\n\tFigure4.m - runtime plot\n\tFigure5.m - graphon estimation of soc-Epinion1 and ca-astroph network\n\tTable2.m  - mean squared error (average and standard deviation) of SAS, USVT and SBA.\n\n4. Compared Methods\n\t(i)   stochastic_block.m (Stochastic Blockmodel Approximation, Airoldi et al. 2013)\n\t(ii)  usvt.m             (Universal Singular Value Thresholding, Chatterjee 2012)\n\n\n\t\nReferences\n[1] E. M. Airoldi, T. B. Costa, and S. H. Chan, \"Stochastic blockmodel approximation of a graphon: Theory and consistent estimation\", Advances in Neural Information Processing Systems. ArXiv: 1311.1731. 2013.\n\n[2] S. Chatterjee. Matrix estimation by universal singular value thresholding. ArXiv:1212.1247. 2012.\n\n\n================================================\nCOPYRIGHT (C) 2014 Stanley Chan and Edoardo Airoldi\n\nThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.\n\nThis program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.\n\nYou should have received a copy of the GNU General Public License along with this program.  If not, see \u003chttp://www.gnu.org/licenses/\u003e.\n\n\n\n\n================================================\nPlease report bugs to Stanley Chan schan@seas.harvard.edu\n\nLast update: January 10, 2014\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fairoldilab%2Fsas","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fairoldilab%2Fsas","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fairoldilab%2Fsas/lists"}