
## On Sufficient Graphical Models
Bing Li, Kyongwon Kim
Keywords: 
JMLR/2024/Proceedings/230893 - On Sufficient Graphical Models.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?_

[3]

The authors link their implementation in section 6 (https://github.com/kyongwonkim/Sufficient-Graphical-Model). There is no readme. Few comments.

### 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]

(3/3)

The authors use simulated data and provide the parameters and definitions in section 6. Its not available in the code. The authors also use the DREAM 4 challenge on which they provide a description and citations. For this no link is provided. 

### 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?_

[5]

The authors refer for the four kernel parameters to formulae (theoretical foundation). However there are more hyperparameters, and define most of it informally, and a lot of it is left to find out for the reader.

### 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 computed the average ROC curves over 50 samples. They show the results over various values of n.

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

[9]

Requires expertise on graphical models and kernel hilbert space.
