What does 'epochs_per_sample', 'epochs_of_next_sample' and 'epochs_per_negative_sample' mean in the`optimize_layout()` function?
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Description
Source code in `optimize_layout()` function:
According to [this page](https://jlmelville.github.io/smallvis/theory.html). The gradient is
1. Where is the term `Vij` in the the source code?
2. What does `epochs_per_sample`, `epochs_of_next_sample` and `epochs_per_negative_sample` mean in the`optimize_layout()` function?
Anyone can give some hint on this? Thanks!
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Research direction
Start at the `optimize_layout()` function and compare its calculations with the linked smallvis theory page. Trace where `Vij`, `epochs_per_sample`, `epochs_of_next_sample`, and `epochs_per_negative_sample` are used, then document explanations that answer the two questions in the issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100