{"id":18654916,"url":"https://github.com/mynameisvinn/federated-learning","last_synced_at":"2025-04-11T17:31:44.100Z","repository":{"id":54608381,"uuid":"135175456","full_name":"mynameisvinn/federated-learning","owner":"mynameisvinn","description":"tf implementation of federated learning","archived":false,"fork":false,"pushed_at":"2019-05-15T05:52:19.000Z","size":14,"stargazers_count":41,"open_issues_count":1,"forks_count":17,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-03-25T16:44:41.220Z","etag":null,"topics":["federated-learning","machine-learning","tensorflow"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/mynameisvinn.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":"2018-05-28T14:57:24.000Z","updated_at":"2025-02-20T07:36:01.000Z","dependencies_parsed_at":"2022-08-13T21:20:35.013Z","dependency_job_id":null,"html_url":"https://github.com/mynameisvinn/federated-learning","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/mynameisvinn%2Ffederated-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mynameisvinn%2Ffederated-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mynameisvinn%2Ffederated-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mynameisvinn%2Ffederated-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mynameisvinn","download_url":"https://codeload.github.com/mynameisvinn/federated-learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248449811,"owners_count":21105564,"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":["federated-learning","machine-learning","tensorflow"],"created_at":"2024-11-07T07:17:01.915Z","updated_at":"2025-04-11T17:31:40.533Z","avatar_url":"https://github.com/mynameisvinn.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# federated learning\na tensorflow implementation of [\"federated learning: strategies for improving communication efficiency\"](https://ai.google/research/pubs/pub45648).\n\nthe goal is to learn over distributed devices (eg smartphones), where each device holds data that may be (a) non iid, (b) imbalanced, and (c) sparse.\n\n## stochastic variance reduced gradient (svrg)\n[svrg](https://papers.nips.cc/paper/4937-accelerating-stochastic-gradient-descent-using-predictive-variance-reduction.pdf) is core to federated learning. when compared to vanilla sgd, it allows for faster convergence by reducing variance, introduced through small, noisy minibatches.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmynameisvinn%2Ffederated-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmynameisvinn%2Ffederated-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmynameisvinn%2Ffederated-learning/lists"}