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 |