Research of efficient MNIST feature transformations, research zkML-friendly ML models for it, implement in transpiler and examples

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@kpandl 已经在做这个了。

开始于 2023年9月19日。

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描述

The goal is to further improve MNIST performance (classification accuracy and constraint usage). For this, the following milestones need to be completed:

Milestone 1, feature pre-processing techniques

  • Task: Research feature transformations that transform the MNIST images into lower-dimensional features with rich information
  • Deliverable: Python code that performs feature pre-processing, experimental results how valuable the different techniques are for MNIST classification using common ML models
  • Date: Thu, 9/28

Milestone 2, zkML-friendly ML model exploration

  • Task: Research ML models that can classify these features well while being zkml-friendly
  • Deliverable: Prototypical implementation of these models in Leo, estimation of constraint size
  • Date: 10/4

Milestone 3, implementation of further models in the transpiler

  • Task: Implement one (or more) promising models in the zkml Leo transpiler, run MNIST tests with these models
  • Deliverable: Updated python code for the transpiler, Jupyter notebook running MNIST in Leo with the updated transpiler
  • Date: 10/18
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