{"id":20841063,"url":"https://github.com/benchopt/benchmark_huber_l2","last_synced_at":"2025-05-08T22:06:44.681Z","repository":{"id":36961216,"uuid":"375028122","full_name":"benchopt/benchmark_huber_l2","owner":"benchopt","description":"Benchopt benchmark for L2-regularized Huber regression","archived":false,"fork":false,"pushed_at":"2022-11-28T15:12:48.000Z","size":15,"stargazers_count":1,"open_issues_count":0,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-05-08T22:06:38.043Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","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/benchopt.png","metadata":{"files":{"readme":"README.rst","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":"2021-06-08T13:56:20.000Z","updated_at":"2023-04-20T03:29:56.000Z","dependencies_parsed_at":"2023-01-17T08:32:17.137Z","dependency_job_id":null,"html_url":"https://github.com/benchopt/benchmark_huber_l2","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":"benchopt/template_benchmark","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_huber_l2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_huber_l2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_huber_l2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_huber_l2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benchopt","download_url":"https://codeload.github.com/benchopt/benchmark_huber_l2/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253154974,"owners_count":21862622,"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":"2024-11-18T01:18:40.310Z","updated_at":"2025-05-08T22:06:44.638Z","avatar_url":"https://github.com/benchopt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Benchmark for L2-regularized Huber regression\n=============================================\n|Build Status| |Python 3.6+|\n\nBenchopt is a package to simplify and make more transparent and\nreproducible the comparisons of optimization algorithms.\nThis benchmark is dedicated to solver:\n\n$$\\\\min_{w, \\\\sigma} {\\\\sum_{i=1}^n\\\\left(\\\\sigma + H_{\\\\epsilon}\\\\left(\\\\frac{X_{i}w - y_{i}}{\\\\sigma}\\\\right)\\\\sigma\\\\right) + \\\\alpha {\\\\|w\\\\|_2}^2}$$\n\nwhere $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features\n\n\n$$y \\\\in \\\\mathbb{R}^n, \\\\quad X \\\\in \\\\mathbb{R}^{n \\\\times p}$$\n\nand\n\n$$\nH_{\\\\epsilon}(z) = \\\\begin{cases} z^2 \u0026 \\\\text {if } \\\\vert z \\\\vert \u003c \\\\epsilon, \\\\\\\\ 2 \\\\epsilon \\\\vert z \\\\vert - \\\\epsilon^2 \u0026 \\\\text{otherwise} \\\\end{cases}\n$$\n\n\nInstall\n--------\n\nThis benchmark can be run using the following commands:\n\n.. code-block::\n\n   $ pip install -U benchopt\n   $ git clone https://github.com/benchopt/benchmark_huber_l2\n   $ cd benchmark_huber_l2\n   $ benchopt run .\n\nApart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:\n\n.. code-block::\n\n\t$ benchopt run . -s sklearn -d simulated --max-runs 10 --n-repetitions 10\n\nUse ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.\n\n.. |Build Status| image:: https://github.com/benchopt/benchmark_huber_l2/workflows/Tests/badge.svg\n   :target: https://github.com/benchopt/benchmark_huber_l2/actions\n.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue\n   :target: https://www.python.org/downloads/release/python-360/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_huber_l2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenchopt%2Fbenchmark_huber_l2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_huber_l2/lists"}