{"id":21678812,"url":"https://github.com/lucasbotang/gradient_descent_for_convex_quadratic","last_synced_at":"2025-04-12T05:38:00.350Z","repository":{"id":162696083,"uuid":"247536529","full_name":"LucasBoTang/Gradient_Descent_for_Convex_Quadratic","owner":"LucasBoTang","description":"Implement the classical gradient descent method using different step size rules","archived":false,"fork":false,"pushed_at":"2020-03-15T19:47:49.000Z","size":30,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-04-12T05:37:50.828Z","etag":null,"topics":["gradient-descent","nonlinear-optimization"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LucasBoTang.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-03-15T19:27:08.000Z","updated_at":"2022-09-01T05:16:12.000Z","dependencies_parsed_at":null,"dependency_job_id":"d325316b-00a4-4dd9-a4ff-c2f3ac360c67","html_url":"https://github.com/LucasBoTang/Gradient_Descent_for_Convex_Quadratic","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/LucasBoTang%2FGradient_Descent_for_Convex_Quadratic","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LucasBoTang%2FGradient_Descent_for_Convex_Quadratic/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LucasBoTang%2FGradient_Descent_for_Convex_Quadratic/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LucasBoTang%2FGradient_Descent_for_Convex_Quadratic/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LucasBoTang","download_url":"https://codeload.github.com/LucasBoTang/Gradient_Descent_for_Convex_Quadratic/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248525167,"owners_count":21118616,"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":["gradient-descent","nonlinear-optimization"],"created_at":"2024-11-25T14:41:37.399Z","updated_at":"2025-04-12T05:38:00.333Z","avatar_url":"https://github.com/LucasBoTang.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Gradient Descent for Convex Quadratic Function\n\nGradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function.\n\n## Method\n\n3 different gradient descent method are implmented:\n\n- Constant Step Size: Gradient descent with fixed step size 0.3\n\n- Exact Line Search: Gradient descent with exact line search is a variant of gradient descent where we perform an exact line search along the line of the gradient vector to move to the point of global minimum along that line.\n\n- Armijo: Gradient descent with Armijo rule\n\n## Performence\n\n\u003cp align=\"center\"\u003e\u003cimg width=\"75%\" src=\"image/descent.png\" /\u003e\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flucasbotang%2Fgradient_descent_for_convex_quadratic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flucasbotang%2Fgradient_descent_for_convex_quadratic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flucasbotang%2Fgradient_descent_for_convex_quadratic/lists"}