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                                            Chaoyang He

Does vertical federated learning of FedML support users to develop deep learning models?

@zhangzhen-8965 we are working on customizing DNN model under VFL. When do you need it?

Does vertical federated learning of FedML support users to develop deep learning models?

@zhangzhen-8965 At that time, it should be ready for you to use.

Can you provide an example of grpc？

@canhongpoxiao try this one: https://github.com/FedML-AI/FedML/tree/master/python/examples/cross_silo/grpc_fedavg_mnist_lr_example

Pip install with simple example

@alex-liang-kh please have a look.

Could you add more servers in FedAvg for faster training speed?

BytePS is for data center-based distributed training, while FedML (e.g., FedAvg) is edge-based distributed training. The particular assumptions of FL include: 1. heterogeneous data distribution cross devices (non-I.I.D.) 2. resource...

Could you add more servers in FedAvg for faster training speed?

@wizard1203 Thanks for your suggestion. As for acceleration, FedML is the only research-oriented FL framework that supports cross-machine multiple GPU distributed training. To further accelerate, we can definitely use many...

Could you add more servers in FedAvg for faster training speed?

> FedML supports multiple parameter servers for the communication efficiency via hierarchical FL and decentralized FL . > In hierarchical FL, there are group parameter servers that split the total...

Could you add more servers in FedAvg for faster training speed?

> @chaoyanghe Thanks for your detailed explanation. Maybe I can try to complete it by myself, and when I finish it I would like to push it to your master...

Could you add more servers in FedAvg for faster training speed?

@wizard1203 Do you mean modifying based on this code? https://github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedavg

Is the MLOps Platform open source? Or can I run the platform on my own server?

@BESTTOOLBOX we do support deploying the server aggregator in self-hosted environment. Please check the CLI command at: https://doc.fedml.ai/mlops/api.html ``` # login as edge server with local pip mode: fedml login...