
## FedSoft: Soft Clustered Federated Learning with Proximal Local Updating
Yichen Ruan, Carlee Joe-Wong
Keywords: Machine Learning (ML)
AAAI/2022/Proceedings/20785 - FedSoft: Soft Clustered Federated Learning with Proximal Local Updating.pdf

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[9]

No Github found + 4
2.A no language mentioned + 4
B. Pseudocode available +0
Figures describing the procedure not available +1
C. comparison to other methods could get part of implementation from there -1

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[4]

(2/3)

2/3 -CIFAR 10 EMNIST synthetic
CIFAR 10
Cost +0 Well known publicly available dataset

EMNIST 
Variation of MNIST?
No direct Link but Citation given +1
Description given +0
Statistics given +0
partially private due to modification +1

Synthetic:
No direct Link or Citation or implementation +5 
Environment not clearly stated (no seed given) +2
Generation parameters are clearly stated +0

Avg: 4

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[3]

1. Hyperparameters detailed in text for algorithm +1
2. Hyperparameter stated clearly in text +0
3. Strategy clear. Budget unclear +1

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[6]

1. Metrics are standard +0
2. Data not clear for one table +1
unclear split +2
3. unclear strategy +2
4. results are aggregated clearly +0

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[6]

Needs expertise in federated and distributed learning aswell as basic machine learning. Algorithm should be reproduceable without that much expertise. exact results i expect to be harder
because one has to assume what the authors 
