ML Artifacts Ownership Enforcement

Yan Yan, Facebook

Abstract: 

This talk is about Machine Learning Artifacts Ownership Enforcement. Privacy is the first priority for machine learning. Building ML artifacts ownership is the first step to ensure it. My talk is about challenges and solutions we had to enforce ML Artifacts ownership.

Yan Yan, Facebook

Yan Yan has been a production engineer in Facebook for 2+ years, focusing on solving Ads machine learning operational challenges with tooling and services. Before Facebook, Yan graduated from UCLA with master degree of computer science.

OpML '20 Open Access Sponsored by NetApp

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@conference {256670,
author = {Yan Yan},
title = {{ML} Artifacts Ownership Enforcement},
year = {2020},
publisher = {USENIX Association},
month = jul
}

Presentation Video 
Teaser
Full