Alternatives and similar repositories for dp-xgboost

Users that are interested in dp-xgboost are comparing it to the libraries listed below

• yuxiangw / autodp
  autodp: A flexible and easy-to-use package for differential privacy
  ☆275Updated last year
• awslabs / privacy-preserving-xgboost-inference
  Privacy-preserving XGBoost Inference
  ☆50Updated 2 years ago
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆33Updated 5 months ago
• vaikkunth / PrivacyFL
  A Simulator for Privacy Preserving Federated Learning
  ☆96Updated 4 years ago
• mc2-project / secure-xgboost
  Secure collaborative training and inference for XGBoost.
  ☆106Updated 3 years ago
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆135Updated 3 months ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆135Updated 2 years ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆74Updated last year
• mc2-project / federated-xgboost
  Federated gradient boosted decision tree learning
  ☆68Updated 2 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆152Updated 2 years ago
• microsoft / msrflute
  Federated Learning Utilities and Tools for Experimentation
  ☆191Updated last year
• BorealisAI / private-data-generation
  A toolbox for differentially private data generation
  ☆131Updated 2 years ago
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆50Updated 7 years ago
• OpenMined / PyVertical
  Privacy Preserving Vertical Federated Learning
  ☆219Updated 2 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆33Updated 4 years ago
• Koukyosyumei / AIJack
  Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
  ☆409Updated last month
• facebookresearch / Opacus-lab
  Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy
  ☆18Updated last year
• Billy1900 / Awesome-Differential-Privacy
  Differential private machine learning
  ☆195Updated 3 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆123Updated this week
• ryan112358 / mbi
  A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.
  ☆108Updated last month
• QinbinLi / DPBoost
  Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)
  ☆27Updated 2 years ago
• privacytrustlab / ml_privacy_meter
  Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
  ☆684Updated 6 months ago
• sunblaze-ucb / dpml-benchmark
  This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.
  ☆63Updated 7 years ago
• spring-epfl / synthetic_data_release
  ☆41Updated 2 years ago
• opendp / smartnoise-sdk
  Tools and service for differentially private processing of tabular and relational data
  ☆285Updated 3 months ago
• pps-lab / rofl-project-code
  ☆34Updated 2 years ago
• cmla-psu / statdp
  Statistical Counterexample Detector for Differential Privacy
  ☆28Updated last year
• ftramer / Handcrafted-DP
  ☆80Updated 3 years ago
• OpenMined / PyDP
  The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
  ☆540Updated last week
• dpcomp-org / dpcomp_core
  ☆45Updated 4 years ago