18 lines
963 B
Markdown
18 lines
963 B
Markdown
---
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tags:
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- '#readingnotes'
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- '#projects/proposals'
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- '#machinelearning'
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---
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The factors that compromise the reproducibility of ML experiments are manifold including the following ones:
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- Unavailability or outdated source code
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- Unavailability of the datasets used for training and evaluation
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- Unavailability of the reference implementation
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- Unclear or missing description of the parameters that need to be set for obtaining the presented results
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- Missing guidelines on the selection of the training, test and evaluation data
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- Missing information of the required libraries/packages and their corresponding version
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- Possible tweaks performed in the source code and that are not mentioned in the paper
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- Missing information about the underpinning techniques, which have been used
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- Lack of documentation about the preprocessing phases, like data preparation and cleaning
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- Hardware requirements that could be not satisfied to train the large neural network |