隐私计算benchmark地址如下: https://github.com/tf-encrypted/tf-encrypted/tree/master/examples/benchmark TF-Encrypted(TFE)简介 这个benchmark基于 TFE 框架来实现,这里对该框架做一个简单的介绍。TFE 是在 TensorFlow 上构建的隐私计算框架,充分利用了 TF 中已有的图计算优化、网络通信和优化等特点,让开发者仅...
Now, TF Encrypted is based on tensorflow 2 ! TF1 execute computation by building a graph first, then run this graph in a session. This is hard to use for a lot of developers, especially for researchers not major in computer science. Therefore, TF1 has very few users and is not maintaine...
TFE 是在 TensorFlow 上构建的隐私计算框架,充分利用了 TF 中已有的图计算优化、网络通信和优化等特点,让开发者仅需关注隐私计算协议的功能层和应用层,是最早出现的一批支持安全多方计算+机器学习的隐私计算框架之一,其开源实现也影响了后续兴起的多个相关框架。TFE的创始成员来自Cape Privacy,但目前主力维护工作主要由...
TF-Encrypted(TFE)简介 这个benchmark基于 TFE 框架来实现,这里对该框架做一个简单的介绍。TFE 是在 TensorFlow 上构建的隐私计算框架,充分利用了 TF 中已有的图计算优化、网络通信和优化等特点,让开发者仅需关注隐私计算协议的功能层和应用层,是最早出现的一批支持安全多方计算+机器学习的隐私计算框架之一,其开源实...
Now, TF Encrypted is based on tensorflow 2 ! TF1 execute computation by building a graph first, then run this graph in a session. This is hard to use for a lot of developers, especially for researchers not major in computer science. Therefore, TF1 has very few users and is not maintaine...