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Hi,
runArgs = {
"iterations" : 2000, # NULL defaults to (max available - 1)
"trials" : 5, # 5 recommended for the dummy dataset
}
My understanding on trials is that, while performing …
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could u provide the hyperparameters on the other datasets besides the VOT and OTB? i want to take the siamban as baseline.
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### Describe the feature or idea you want to propose
The [`PyODAdapter`](https://github.com/aeon-toolkit/aeon/blob/main/aeon/anomaly_detection/_pyodadapter.py) in aeon allows us to use any outlie…
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### Describe the feature or idea you want to propose
The [`PyODAdapter`](https://github.com/aeon-toolkit/aeon/blob/main/aeon/anomaly_detection/_pyodadapter.py) in aeon allows us to use any outlier …
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I implement a `ConditionedConfigurationSpace` that supports complex conditions between hyperparameters (e.g., x1 = 100:
return False
return True
# return config['x1']
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Adding the **timeout** parameter to the .fit() method, that should force the library to return best known solution found so far as soon as provided number of seconds since the start of training are pa…
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Hello! I've been trying to replicate the results on Sachs using the provided hyperparameters, but I'm getting SHD ~37-40 instead of the low 10s. Any clue why?
```
from cdt.data import load_dataset…
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I pretrained both BERT uncased as well as BERT cased models using the same hyperparameters(for uncased model) on Wikipedia and BookCorpus, but the BERT cased models perform worse than the google check…
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@Jordan-Pierce I’m really excited to see all the improvements you’ve been making to CoralNet-toolbox! I also noticed the change of the working branch to dev—great move.
The addition of the link to …
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https://www.pytorchlightning.ai/blog/using-optuna-to-optimize-pytorch-lightning-hyperparameters