[FedML HE] "Is the reason homomorphic encryption algorithms are time-consuming for deep learning because deep learning models have too many parameters and these parameters also need to be encrypted?"

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Description

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Contributor guide

Research direction

Investigate the computational complexity of homomorphic encryption algorithms and how they scale with the number of model parameters in deep learning.

Tech stack

python

Domain

machine learning

Issue type

Research

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

2

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

1-3 hours

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

Fresh

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

Clear

Prerequisites

Python

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

75