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Congratulations on your paper! While I was looking through it, I was disappointed to see that my efforts on GPU accelerated Layer-Neighbor Sampling were neither mentioned nor cited in your paper.
I…
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### What is the problem you're trying to solve
I'm very interested in finding the right balance of compression between zstd, gzip, and different levels of compression to reduce the startup time of …
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@ptiede @anilipour
I'm thinking about the possibility of adding more probabilistic versions of some regularizers. For instance,
- L1-norm can be interpreted as each pixel intensity is following a…
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de Jong has a fast algorithm for sampling x from the conditional distribution.
There are better algorithms for the unconditional distribution too.
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### Background
Sampling without replacement is a core operation. There are a handful of useful algorithms, depending on the shape of the problem, some of which are not easy to implement.
I recen…
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[Graph neural bayesian optimization for virtual screening](https://openreview.net/forum?id=t3PzfH98Mq)
```bib
@inproceedings{wang2023graph,
title={Graph neural bayesian optimization for virtual…
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Support for additional OPE algorithms such as weighted importance sampling, doubly robust.
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Add progress bar for cluster algorithms. Try to improve performance of GMM by sampling less when creating training set for fitting. Maybe allow users to select sample resolution.
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Currently, the `sample` function runs in `O(k)` (k being sample size) time but in `O(n)` (n being the size of the population). This can be awful for algorithms sampling large lists frequently (k-means…
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**Ideas for modules:**
- [ ] Sampling Algorithms (based in 2020 SPSS and Yves Tillé book).
- [ ] Survey Design
- [ ] Survey Analysis
- [ ] Survey Documentation
** Package Administration…