Over-the-Air Ensemble Inference with Model Privacy

Related tags

Deep Learning oac-based-private-ensembles
Overview

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
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