{"id":18800574,"url":"https://github.com/xtra-computing/privml","last_synced_at":"2026-01-25T13:01:58.954Z","repository":{"id":86257258,"uuid":"235282642","full_name":"Xtra-Computing/PrivML","owner":"Xtra-Computing","description":null,"archived":false,"fork":false,"pushed_at":"2021-01-08T03:29:00.000Z","size":28664,"stargazers_count":19,"open_issues_count":0,"forks_count":2,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-05-21T20:46:44.671Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"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/Xtra-Computing.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-01-21T07:42:32.000Z","updated_at":"2024-10-16T03:41:52.000Z","dependencies_parsed_at":null,"dependency_job_id":"31755062-ddb3-457c-b645-acc5f6832732","html_url":"https://github.com/Xtra-Computing/PrivML","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Xtra-Computing/PrivML","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xtra-Computing%2FPrivML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xtra-Computing%2FPrivML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xtra-Computing%2FPrivML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xtra-Computing%2FPrivML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Xtra-Computing","download_url":"https://codeload.github.com/Xtra-Computing/PrivML/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xtra-Computing%2FPrivML/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28753411,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-25T10:25:12.305Z","status":"ssl_error","status_checked_at":"2026-01-25T10:25:11.933Z","response_time":113,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":[],"created_at":"2024-11-07T22:19:08.618Z","updated_at":"2026-01-25T13:01:56.548Z","avatar_url":"https://github.com/Xtra-Computing.png","language":null,"readme":"# Private Machine Learning\n\n## Table of Contents\n* [Overview](#overview)\n* [Project Descriptions](#project-descriptions)\n* [Publications](#publications)\n\n## Overview\n\nThis repo summarizes the private machine learning work of Xtra group. Currently we work mainly on two areas: federated learning and differential privacy. Federated learning enables the collaborative learning of multiple parties without exchanging the local data.\n\n## Project Descriptions\n\nWe have worked/are working on the following projects.\n\n(1) [Federated Learning Survey](#FL_survey): We conducted a survey on federated learning systems.\n\n(2) [Federated Gradient Boosting Decision Trees](#SimFL): We designed a novel federated learning framework for gradient boosting decision trees.\n\n(3) [Differentially Private Gradient Boosting Decision Trees](#DPBoost): We designed a differentially private gradient boosting decision tree training algorithm.\n\n(4) [Federated Learning Benchmarks](#OARF): We designed a benchmark for evaluating the components in different FL systems.\n\n## Publications\n\n* [A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection](https://qinbinli.com/files/FLSurvey.pdf) \u003cbr\u003e\nQinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Bingsheng He\u003cbr\u003e\n\u003ci\u003earXiv preprint\u003c/i\u003e\n    * We conducted a comprehensive analysis against existing federated learning systems from different aspects (see [details](FL_survey)).\n\n* [Practical Federated Gradient Boosting Decision Trees](https://arxiv.org/abs/1911.04206) \u003cbr\u003e\nQinbin Li, Zeyi Wen, Bingsheng He\u003cbr\u003e\n\u003ci\u003eThirty-Fourth AAAI Conference on Artificial Intelligence\u003c/i\u003e. \u003cb\u003eAAAI 2020\u003c/b\u003e.\n    * We proposed a novel federated learning framework for gradient boosting decision trees by exploiting similarity (see [details](SimFL)).\n\n* [Privacy-Preserving Gradient Boosting Decision Trees](https://arxiv.org/abs/1911.04209)  \u003cbr\u003e\nQinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He\u003cbr\u003e\n\u003ci\u003eThirty-Fourth AAAI Conference on Artificial Intelligence\u003c/i\u003e. \u003cb\u003eAAAI 2020\u003c/b\u003e.\n    * We designed a new differentially private gradient boosting decision trees training algorithm (see [details](DPBoost)).\n\n* [The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems](https://arxiv.org/abs/2006.07856)  \u003cbr\u003e\nSixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He\u003cbr\u003e\n\u003ci\u003earXiv preprint\u003c/i\u003e.\n    * We designed a benchmark for evaluating the components in different FL systems (see [details](OARF), [code](https://github.com/Xtra-computing/OARF)).\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxtra-computing%2Fprivml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxtra-computing%2Fprivml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxtra-computing%2Fprivml/lists"}