diff --git a/docs/conf.py b/docs/conf.py index 6b17386a..2c2a5d4c 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -131,4 +131,5 @@ nb_execution_excludepatterns = [ # Slow notebook 'notebooks/deep_learning/*.*', + 'notebooks/implicit_diff/dataset_distillation.*', ] \ No newline at end of file diff --git a/docs/notebooks/implicit_diff/plot_dataset_distillation.ipynb b/docs/notebooks/implicit_diff/dataset_distillation.ipynb similarity index 99% rename from docs/notebooks/implicit_diff/plot_dataset_distillation.ipynb rename to docs/notebooks/implicit_diff/dataset_distillation.ipynb index ede29bd1..3a1b1ab7 100644 --- a/docs/notebooks/implicit_diff/plot_dataset_distillation.ipynb +++ b/docs/notebooks/implicit_diff/dataset_distillation.ipynb @@ -15,9 +15,7 @@ "\n", "Dataset distillation [Maclaurin et al. 2015](https://arxiv.org/pdf/1502.03492.pdf), [Wang et al. 2020](https://arxiv.org/pdf/1811.10959.pdf) aims to learn a small synthetic\n", "training dataset such that a model trained on this learned data set achieves\n", - "small loss on the original training set.\n", - "\n", - "[*Mathieu Blondel*](https://mblondel.org/), [*Fabian Pedregosa*](https://fa.bianp.net)" + "small loss on the original training set." ] }, { @@ -238,7 +236,7 @@ "outputs": [ { "data": { - "image/png": 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" ] diff --git a/docs/notebooks/implicit_diff/plot_dataset_distillation.md b/docs/notebooks/implicit_diff/dataset_distillation.md similarity index 97% rename from docs/notebooks/implicit_diff/plot_dataset_distillation.md rename to docs/notebooks/implicit_diff/dataset_distillation.md index 72cdc420..a78348a4 100644 --- a/docs/notebooks/implicit_diff/plot_dataset_distillation.md +++ b/docs/notebooks/implicit_diff/dataset_distillation.md @@ -5,7 +5,7 @@ jupytext: extension: .md format_name: myst format_version: 0.13 - jupytext_version: 1.13.6 + jupytext_version: 1.13.8 kernelspec: display_name: Python 3 name: python3 @@ -24,8 +24,6 @@ Dataset distillation [Maclaurin et al. 2015](https://arxiv.org/pdf/1502.03492.pd training dataset such that a model trained on this learned data set achieves small loss on the original training set. -[*Mathieu Blondel*](https://mblondel.org/), [*Fabian Pedregosa*](https://fa.bianp.net) - +++ {"id": "T_1ezvj0ut0L"} **Bi-level formulation**