Differential privacy in machine learning
With a surge in the use of machine learning, stakeholders have no visibility into the activities of processes that were run on their private data. When it comes to sharing data to train these machine learning models, there is a rising concern about privacy. Federated learning was introduced as a...
Saved in:
Main Author: | Tan, Nicole |
---|---|
Other Authors: | Anupam Chattopadhyay |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156368 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
Similar Items
-
Fintech related machine learning : credit risk analysis using machine learning models
by: Ng, Zaphyr Wee Hau
Published: (2021) -
Machine learning for industrial IOT
by: Yeow, Brandon Wei Liang
Published: (2023) -
Driving style recognition with privacy protection
by: Seet, Jonathan Wei Han
Published: (2021) -
Artificial intelligence/machine learning for wealth management
by: Teo, Wee Ren
Published: (2022) -
Deep machine learning based scene understanding
by: Wo, Benjamin Shun Xian
Published: (2022)