From 2a2c4f6700f226d3f3566abaa33541f983de20a2 Mon Sep 17 00:00:00 2001 From: Zinan Lin Date: Thu, 5 Dec 2024 19:20:05 -0800 Subject: [PATCH] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 3af5417..82d485d 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ This repo is a Python library to **generate differentially private (DP) synthetic data without the need of any ML model training**. It is based on the following papers that proposed a new DP synthetic data framework that only utilizes the blackbox inference APIs of foundation models (e.g., Stable Diffusion, GPT models). -* Differentially Private Synthetic Data via Foundation Model APIs 1: Images +* **Differentially Private Synthetic Data via Foundation Model APIs 1: Images** [[paper (ICLR 2024)]](https://openreview.net/forum?id=YEhQs8POIo) [[paper (arxiv)](https://arxiv.org/abs/2305.15560)] **Authors:** [[Zinan Lin](https://zinanlin.me/)], [[Sivakanth Gopi](https://www.microsoft.com/en-us/research/people/sigopi/)], [[Janardhan Kulkarni](https://www.microsoft.com/en-us/research/people/jakul/)], [[Harsha Nori](https://www.microsoft.com/en-us/research/people/hanori/)], [[Sergey Yekhanin](http://www.yekhanin.org/)] @@ -10,9 +10,9 @@ This repo is a Python library to **generate differentially private (DP) syntheti ## Documentation Please refer to the [documentation](https://microsoft.github.io/DPSDA/) for more details, including the installation instructions, usage, and examples. -## Attention +## News -The code that was published along with the [paper](https://arxiv.org/abs/2305.15560) has been moved to the [deprecated](https://github.com/microsoft/DPSDA/tree/deprecated) branch on 11/21/2024, which is no longer maintained. The code in the current main branch is a refactored version of the original codebase, which is more modularized and easier to use, with support of more advanced Private Evolution algorithms and APIs. +* `11/21/2024`: The refactored codebase for image generation has been released. It is completely refactored to be more modular and easier to use and extend. The code originally published with the [paper](https://arxiv.org/abs/2305.15560) has been moved to the [deprecated](https://github.com/microsoft/DPSDA/tree/deprecated) branch, which is no longer maintained. ## Contributing