Over-the-Air Ensemble Inference with Model Privacy

This repository contains simulations for our private ensemble inference method.

Installation

• Install conda and torch manually (recommended)
• pip install -r requirements.txt

Running

• First train and cache the device models.
• Then you can generate figures, tables or run raw experiments.

Training CV models

• python train.py --data --num_repeats 10 --num_devices 20 --num_epochs 50
• can be cifar10, cifar100, mnist, fashionmnist

Training NLP models

• python nlp_train.py --data --num_repeats 10 --num_devices 20
• can be yelp_review_full, yelp_polarity, imdb, emotion

Running an Experiment

• See the bottom of ota_private_ensemble.py

Generating TeX Code for the Comparison table

• Run python figure_comparison_table.py

### Generate TeX Code for the Varying Conditions pgfplot

• Run python figure_conditions.py