Machine Unlearning with SISA - EC523 with Prof. Kayhan Batmanghelich

[link to our report]

Harshil Gandhi, GM Harshvardhan, Shaunak Joshi

This is our improvements to the original implementation of SISA Machine Unlearning paper.

We have made improvements using 2 approaches:

1. Greedy Distribution-Aware Sharding: In the branch named "Approach-1"
2. Clustering similar data points: In the branch named "Approach-2"

You can start running experiments by having a look at the readme in the purchase example folder at example-scripts/purchase-sharding.

sisa.py is the script that trains a given shard. It should be run as many times as the number of shards.