
## Sampling Permutations for Shapley Value Estimation
Rory Mitchell, Joshua Cooper, Eibe Frank, Geoffrey Holmes
Keywords: 
JMLR/2022/Proceedings/210439 - Sampling Permutations for Shapley Value Estimation.pdf
Project URL: nan

### 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?_

[10]

No implementation given.

### 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?_

[3]

(7/7)

The authors provide details and citations on the tabular datasets used in table 2. They also use ImageNet and provide a citation. No direct links or descriptions.

### 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]

The authors state the input in algorithm 1, 2, 3 and 4. The authors state the parameters of the used methods in sec 5. (default parameters, listed). The other algorithm parameters are stated informally in the text but no acquisition specified.

### 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?_

[1]

The authors state in 5.1. no data split is used. Metric is MSE (eq 15), discrepancy and time and permutation time (presented with mean and std). 

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

[8]

Requries expertise on quasi monte carlo methods.
