Speaker: Dr.Georgios Kaisssis, MHBA Video Link: https://www.youtube.com/watch?v=F46lX5VIoas&t=21m50s Motivation:AI in medical imaging
Providing encryption to data is good, but to allow working on the encrypted data can be much more beneficial. Here, we explain the concept of Functional Encryption and give a brief comparison with Homomorphic Encryption.
This blog post summarises Fatemeh's Talk on privacy preserving NLP, showing the threats and mitigations with vulnerabilities in the NLP pipeline.
The Reviewed Paper: Preserving Differential Privacy in Convolutional Deep Belief Networks (ðAuthors: Nhat Hai Phan, Xintao Wu, Dejing Dou)
Fifth part of the series CKKS explained where we see how to define rescaling
Across research institutions, personal devices, and private companies, humankind is gathering a huge amount of information about ourselves a
Dr. Helen Nissenbaum is one of the worldâs most influential philosophers in the privacy space. She is the author of âPrivacy in Context: Tec
New paradigms and skills are spread most effectively through education, so weâre building an entirely new learning platform starting with a series of courses on privacy-preserving machine learning.
The delayed results in the 2020 U.S. election has fueled accusations of fraud, which may yet spill into civil unrest. This blog looks at e-voting as a possible solution to the problems at the heart of this election.
Learn from data, without sacrificing privacy.
It is a challenging task to acquire medical data for the deep learning models to train on. This blog gives a demo of how we can use Federated Learning to train our model on additional data without compromising the privacy of that data.
Fourth part of the series CKKS explained where we see how to define ciphertext multiplication and relinearization
We're proud to announce that OpenMined was recently mentioned in the State of AI Report 2020. Since OpenMined's inception in 2017, the commu
Interview with Chris Briggs, OpenMined's Featured Contributor for October 2020!
In this tutorial, you are going to learn how to setup PySyft, a privacy-preserving machine learning framework, on Windows 10.
Our mission at OpenMined is to make the world more privacy-preserving by lowering the barrier-to-entry to privacy-preserving technologies th
This post is part of our Privacy-Preserving Data Science, Explained series. With the advancements in the field of Artificial Intelligence, o
We use Opacus from PyTorch and PySyft from OpenMined to combine Federated Learning with Differential Privacy.
Interview with the Beta Bootcamp Tech Team, OpenMined's Featured Contributors for September 2020!
OpenMined aims to lower the barrier to entry in privacy preserving AI by offering a substantial fee free learning opportunity that can poten
Meaningful privacy and how it is applied in technology will be the focus of 60 privacy preserving leaders from around the globe during the
OpenMined has built vibrant relationships with numerous startups, who are leveraging privacy AI technologies as a core part of their offer
There is a good chance you are reading this article on a laptop, tablet, or smartphone. There is an even greater chance that thanks to a wo
