Boosting the Cross-Architecture Generalization of Dataset Distillation through an Empirical Study (ELF)

Getting Started

First, download our repo:

git clone https://github.com/paper-code-anonymous/ELF.git
cd ELF

For an express instillation, we include .yaml files that you can run

conda env create -f requirements.yaml

You can then activate your conda environment with

conda activate ELF

Generate synthetic dataset

Below are some example commands to run each method, you can run one of them to generate synthetic dataset for eval using ELF.

Distillation with Distribution Matching

The following command will generate synthetic dataset using DM method.

sh distill_DM.sh

Distillation with Differentiable Siamese Augmentation

The following command will generate synthetic dataset using DSA method.

sh distill_DSA.sh

Distillation with Matching Training Trajectories

The following command will generate buffer for MTT method to distillation.

sh buffer_MTT.sh

The following command will generate synthetic dataset using MTT method.

sh distill_MTT.sh

Eval using ELF

The following command will generate buffer for ELF to get features.

sh ELF_buffer.sh

The following command will eval synthetic dataset using ELF method.

sh ELF_eval.sh