
## Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling
Ye He, Tyler Farghly, Krishnakumar Balasubramanian, Murat A. Erdogdu
Keywords: 
JMLR/2024/Proceedings/221198 - Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling.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?_

[9]

The authors state the package used for their experiments in section 7. 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?_

[6]

(2/2)

The authors evaluate the method on simulation using the formula specified in equation 10. The parameters are specified as well for the simulation. It is unclear if the implementation is given in the specified package.

### 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?_

[4]

Hyperparmaeters are informally summarised in section 7. No acquisition or overview.

### 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 use first coordinate, second coordiante and wassertein-2 distance for their evaluations. The variance is standard error over 500 runs and the aggregation is average. Data split not applicable.

### 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 discretized ito diffusion and complexity of sampling.
