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https://arxiv.org/pdf/1607.08316.pdf
https://github.com/ilija139/HORD
Would this be possible to implement as a new feature?
It seems to perform better than other bayesian optimization methods…
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hi here,
I got the following error when run trainer.hyperparameter_search() on databricks:
RuntimeError: CUDA out of memory. Tried to allocate 300.00 MiB (GPU 0; 11.17 GiB total capacity; 10.18 GiB …
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Using the frontpage complete MNIST example, the below only works if _some_ hyperparameter search is added after Sequential
```
model = Sequential()
model.add(Dense({{choice([100, 200])}})) # Th…
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# 📚 Documentation
** Is there documentation missing? **
Hi!
Spatio-temporal Exact GP:
I am new to this library and I have been checking around on how to use a spatio-temporal GP.
I did not find…
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**Bug Report Checklist**
- [x] I provided code that demonstrates a minimal reproducible example.
- [?] I confirmed bug exists on the latest mainline of AutoGluon via source install.
- [x] I c…
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Model optimization needs to be implemented.
A skeleton for a possible iterative workflow that will pursue model optimization would look like this:
1. Define a first model into an initial config…
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Hello, I am trying to clarify whether or not keras_tuner objects such as the BayesianOptimization tuner have the ability to take as input prior hyperparameter combinations (for example, from a gridwis…
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I think it'd be good to have suggested bounds on hyperparameters to help people to choose sensible values. This may also help the optimisation-based approach to selecting hyperparameters (by putting b…
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I would like to use a hyperparameter search algorithm to find the best hyperparameters (L1 and L2). For this I think the last loss value reported by the training algorithm can be useful.
Is there a w…
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Thanks for your wonderful work. Well-organized project!
You have mentioned that you did a grid search on hyperparameters. Could you please provide the best hyperparameters for different datasets? o…