{"id":13633389,"url":"https://github.com/ziyuw/rembo","last_synced_at":"2025-04-18T10:34:47.732Z","repository":{"id":9881887,"uuid":"11884883","full_name":"ziyuw/rembo","owner":"ziyuw","description":"Bayesian optimization in high-dimensions via random embedding.","archived":false,"fork":false,"pushed_at":"2013-08-04T20:55:23.000Z","size":212,"stargazers_count":112,"open_issues_count":3,"forks_count":25,"subscribers_count":10,"default_branch":"master","last_synced_at":"2024-07-28T00:37:25.094Z","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ziyuw.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":"2013-08-04T20:52:59.000Z","updated_at":"2024-05-27T12:53:29.000Z","dependencies_parsed_at":"2022-09-10T05:51:06.905Z","dependency_job_id":null,"html_url":"https://github.com/ziyuw/rembo","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ziyuw%2Frembo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ziyuw%2Frembo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ziyuw%2Frembo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ziyuw%2Frembo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ziyuw","download_url":"https://codeload.github.com/ziyuw/rembo/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":213597600,"owners_count":15610713,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":"2024-08-01T23:00:36.332Z","updated_at":"2024-08-01T23:01:32.654Z","avatar_url":"https://github.com/ziyuw.png","language":"Matlab","funding_links":[],"categories":["AutoML","Profiling","Scheduling","Matlab","Libraries","Tools and projects"],"sub_categories":["Profiling","LLM"],"readme":"## REMBO\nThis package contains code for the paper \"Bayesian Optimization in a Billion \nDimensions via Random Embeddings\". The paper tries to solve the problem of \ndoing Bayesian optimization in high dimensions. For more details please read \nthe paper (http://www.cs.ubc.ca/~ziyuw/papers/rembo.pdf). \n\n### INSTALL\nThe package is written in Matlab. Thus to install, just run startup.m. This \npackage could make use of the function \"fminsearch\" from Matlab. \nThis, however, is not necessary.\n\nTo run the lpsolve example from the paper, please download the data files from:\nhttp://www.cs.ubc.ca/~ziyuw/AC_blackbox_eval.tar.\nAnd untar the data files to the folder /demos/lpsolve/.\n\n### Configuration files\nThis package allows one the specify the parameters settings in \na configuration file. In the configuration file, one can specify\nthe type of parameters to be optimized. \nCurrently, the package supports continuous, discrete, and categorical\nparameters. It also allows one to use log scales. \nFor an example of such a configuration file, please checkout \n\"demos/lpsolve/lpsolve.yaml\".\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fziyuw%2Frembo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fziyuw%2Frembo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fziyuw%2Frembo/lists"}