{"id":15974539,"url":"https://github.com/patwie/robustkernelpaths","last_synced_at":"2025-08-18T18:06:50.692Z","repository":{"id":19821350,"uuid":"23082201","full_name":"PatWie/RobustKernelPaths","owner":"PatWie","description":"ICML paper: Robust and Efficient Kernel Hyperparameter Paths with Guarantees","archived":false,"fork":false,"pushed_at":"2023-01-10T09:21:26.000Z","size":32,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-04T17:12:53.728Z","etag":null,"topics":["eigen","hyperparameters","icml","kernel","kernel-hyperparameter","libsvm","machine-learning","machine-learning-algorithms"],"latest_commit_sha":null,"homepage":"http://patwie.com","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"lgpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/PatWie.png","metadata":{"files":{"readme":"README.md","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":"2014-08-18T18:41:47.000Z","updated_at":"2023-01-12T18:10:28.000Z","dependencies_parsed_at":"2023-01-11T20:36:59.554Z","dependency_job_id":null,"html_url":"https://github.com/PatWie/RobustKernelPaths","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/PatWie/RobustKernelPaths","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PatWie%2FRobustKernelPaths","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PatWie%2FRobustKernelPaths/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PatWie%2FRobustKernelPaths/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PatWie%2FRobustKernelPaths/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/PatWie","download_url":"https://codeload.github.com/PatWie/RobustKernelPaths/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PatWie%2FRobustKernelPaths/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271035487,"owners_count":24688422,"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","status":"online","status_checked_at":"2025-08-18T02:00:08.743Z","response_time":89,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["eigen","hyperparameters","icml","kernel","kernel-hyperparameter","libsvm","machine-learning","machine-learning-algorithms"],"created_at":"2024-10-07T21:42:37.145Z","updated_at":"2025-08-18T18:06:50.657Z","avatar_url":"https://github.com/PatWie.png","language":"C++","readme":"# Robust and Efficient Kernel Hyperparameter Paths with Guarantees\n\n**auto finetuning, svm, parameters, kernel parameter, choose parameters **\n\nThe results of non-linear SVM classifications heavily rely on the choose of the kernel hyperparameter, i.e. , \\lambda in $k(x,y)=\\exp(-\\lambda \\Vert{x-y}\\Vert²)$ in the kernel function.\nThis repository contains an effective algorithmn that calculates an approximate entire solution path of the objective function with respect to the hyperparameter within the interval $[2^{-10},2^{10}]$ without numerical issues by which the exact algorithms suffer.\nMore details can be found in the corresponding [paper][paper]. \n\nFor the matrix calculation the [library Eigen][eigen] was used in combination with [OpenMP][openmp]. The backend solver is [libSVM][libsvm]\n\nThe program reads the problem description in the default libSVM format. See the documented source for more information or run the compiled program without any parameters to get help.\n\n\n### weblinks\n\n * [jmlr](http://jmlr.org/proceedings/papers/v32/giesen14.html) entry\n * [paper](http://jmlr.org/proceedings/papers/v32/giesen14.pdf) pdf format\n\n \n[jmlr]:http://jmlr.org/proceedings/papers/v32/giesen14.html\n[paper]:http://jmlr.org/proceedings/papers/v32/giesen14.pdf\n[eigen]:http://eigen.tuxfamily.org/index.php?title=Main_Page\n[libsvm]:http://www.csie.ntu.edu.tw/~cjlin/libsvm/\n[openmp]:http://openmp.org/wp/\n\n\n\n\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatwie%2Frobustkernelpaths","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpatwie%2Frobustkernelpaths","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatwie%2Frobustkernelpaths/lists"}