Overview
Details
citeseer_node_classification
Federated CIFAR100 classification is a commonly used benchmark in FL. It assumes different virtual clients having non-overlapping samples from CIFAR100 dataset.
model
| Model Name |
Non-Fed Performance |
NumPara |
Implementation |
| cnn |
- |
|
- |
| mlp |
- |
|
- |
supported partitioner
| Name |
IsDefault |
Comments |
| IIDPartitioner |
yes |
|
| DiversityPartitioner |
|
Partitioning according to label diversity |
| DirichletPartitioner |
|
Partitioning according to dir. distribution of labels |
cora_node_classification
Federated MNIST classification is a commonly used benchmark in FL. It assumes different virtual clients having non-overlapping samples from MNIST dataset.
model
| Model Name |
Non-Fed Performance |
NumPara |
Implementation |
| cnn |
- |
|
- |
| mlp |
- |
|
- |
supported partitioner
| Name |
IsDefault |
Comments |
| IIDPartitioner |
yes |
|
| DiversityPartitioner |
|
Partitioning according to label diversity |
| DirichletPartitioner |
|
Partitioning according to dir. distribution of labels |
pubmed_node_classification
Federated CIFAR10 classification is a commonly used benchmark in FL. It assumes different virtual clients having non-overlapping samples from CIFAR10 dataset.
model
| Model Name |
Non-Fed Performance |
NumPara |
Implementation |
| cnn |
- |
|
- |
| mlp |
- |
|
- |
supported partitioner
| Name |
IsDefault |
Comments |
| IIDPartitioner |
yes |
|
| DiversityPartitioner |
|
Partitioning according to label diversity |
| DirichletPartitioner |
|
Partitioning according to dir. distribution of labels |