-
# 【论文笔记】FEDML-HE_AN EFFICIENT HOMOMORPHIC-ENCRYPTION-BASED PRIVACY-PRESERVING FEDERATED LEARNING SYSTEM - P3troL1er 的个人博客
【论文笔记】FEDML-HE_AN EFFICIENT HOMOMORPHIC-ENCRYPTION-BASED PRIVACY-PRESERVING F…
-
![image](https://github.com/FedML-AI/FedML/assets/41562415/f65c3e10-6ea8-442e-acfe-5fd409bcdf86)
fedml.run_simulation()
File "/root/miniconda3/envs/fedml-3.10/lib/python3.10/site-packages/…
-
Dear authors.
I am Chaoyang He (https://chaoyanghe.com/), co-founder of FedML Inc. Thanks for proposing such a benchmark to compare with different frameworks. I like your summarization, but It seem…
-
Automatic rank inference will be used to support the following functions
https://github.com/FedML-AI/FedML/blob/2f842a53adadbb3f09d5360be99f998474d0b802/python/fedml/core/alg_frame/server_aggregato…
ghost updated
7 months ago
-
Hi, I didn't find any code for the training pipeline for federated orthogonal training. The code seems just for FedAvgSeq. Did I miss something?
-
### Discussed in https://github.com/openmlsys/openmlsys-zh/discussions/172
Originally posted by **chaoyanghe** March 22, 2022
Hi OpenMLSys Team,
This is a nice effort. I am also writing a b…
-
### Describe the bug
Hello,
I am trying to RUN fedml simulation on a large number of clients (about 50 in this case, but planning to go until 1000) on a relatively large model (EfficientNet) wi…
-
Dear Dr.Jia,
I attempted to run your code and encountered some questions regarding the calculation of the model's params and FLOPs.
dummy_input = torch.randn(1, 3, 32, 32)
flops, params = profi…
-
Hi, I have found some bugs in `MQTT+s3` module whenI tried to training by partial clients per round.
## **Bug 1: Object of type int64 is not JSON serializable**
```
Traceback (most recent call l…
-
```
PS C:\Users\chaoy\sourcecode\FedML\python> fedml login 201 -v local
login...True, None
c:\users\chaoy\sourcecode\fedml\python\fedml\cli\edge_deployment\client_login.py
PS C:\Users\chaoy\sourcecode…