## Better Embedding and More Shots for Few-shot Learning
Ziqiu Chi, Zhe Wang, Mengping Yang, Wei Guo, Xinlei Xu
Keywords: Machine Learning: Few-shot learning, Computer Vision: Transfer, low-shot, semi- and un- supervised learning, Computer Vision: Machine Learning for Vision, Machine Learning: Classification, Machine Learning: Theory of Deep Learning
IJCAI/2022/Proceedings/0398 - Better Embedding and More Shots for Few-shot Learning.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?_

[10]

A link to the code is no provided in the paper. Therefore, it is not possible to access the code in a straight way. 

### 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 datasets are mentioned with a citation for each and they are popular datasets. However, there are not explained, statistics not 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?_

[4]

The hyperparameter tuning process is explained for each hyperparameter. Also, the hyperparameters of the models are provided. This is detailed in the text, but and overview is missing. The authors do not mention how they obtained these hyperparametes and what was the budget.

### 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 evaluation metric is stated (accuracy) and the evaluation procedure is explained. The data split is explained in detail in the paper. The methodology of the experiments is explained well, so this part is not a problem.

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

[6]

The related work, introduction, and notation are very brief. This can be a problem for readers with no background knowledge as they need to read other papers to understand the work. The methodology of the experiments is explained well, so this part is not a problem.