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## Keyword: differential privacy
### State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey
- **Authors:** Chaoyu Zhang
- **Subjects:** Cryptography an…
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We know that LightGBM currently supports quantile regression, which is great, However, quantile regression can be an inefficient way to gauge prediction uncertainty because a new model needs to be bu…
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I'm having a concern regarding the MBD benchmark. The protocol suggests training on the MP datasets and testing on the WBM dataset. Could you please confirm if "energy above hull" is the correct train…
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Review if the `qnorm()` approach should be used.
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Hi, I noticed that you used **torch.distributions.Distribution** after MLP to get the final output, could you share some insights about this choice? What's the advantage compared with the direct usa…
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The current code uses init_score to inject starting values, but what about modeling problems that need to use init_score to represent an offset, e.g. in insurance, a gamma severity or poisson frequenc…
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I'm having issues getting any models to compile with `enw_model()`, and the error seems to point to an issue with the include paths.
I've tried this a few different ways, but nothing seems to resolve…
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**Describe the bug**
I get output of the form
```
variable mean
lp__ -\033[31m\033[4m1\033[24m49\033[39m\033[31m3\033[39m
beta[1] …
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**Describe the bug**
User defined functions as part of Stan code generated by `brms` fail to compile with `expose_function`, while @rok-cesnovar [`expose_cmdstanr_functions`](https://raw.githubuserco…