OpenMined Featured Contributor: February 2021

Interview with Bala Priya, OpenMined's Featured Contributor for February 2021!

Advances and Open Problems in Federated Learning

Summary of Peter Kairouz’s talk at the OpenMined Privacy Conference 2020.

Scrambling Memorized Info in GPT-2

What do GPT-2 and GPT-3 know about us?

Limitations of Information Flows

To improve information flows, we need to understand what exactly is not working today.

Society Runs on Information Flows

Information flows form the basis society. How can we understand them better? Why are they often broken and how can we possibly fix them?

Why Venture Capitalists are Interested in Privacy Investing Now

This is a conference talk summary from the OpenMined Privacy Conference 2020 Trends and predictions for privacy startups with:Morgan Mahloc

Call to Research Study on Privacy-Preserving AI for Mental Health

“Humans are not perfect. They can get distracted and sometimes miss out on subtle speech cues and warning signs. Unfortunately, there is no

OpenMined Featured Contributor: January 2021

Interview with Helena Barmer, OpenMined's Featured Contributor for January 2021!

Duet Demo - How to do data science on data owned by a different organization

This is a summary of Duet Tutorial by Andrew Trask which was presented at OpenMined Privacy Conference 2020.Brief intro to federated learnin

What's in the TensorFlow Federated (TFF) box?

Summary of Krzysztof Ostrowski’s talk at the OpenMined Privacy Conference 2020

The Lightness of Being Forgotten

The use of my private information has long bothered me. However, I have not done much about the right to be forgotten.

How to Protect Your Privacy Online (right now)?

Since you clicked open the link to this post, may I be so bold as to assume that you, my dear reader, are as concerned about internet privac

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

Summary of Dr.Nicolas Papernot's talk at the OpenMined Privacy Conference 2020.

OpenMined Featured Contributor: December 2020

Interview with Laura Ayre, OpenMined's Featured Contributor for December 2020!

Summary of 'Securing NLP with SyferText' Demo with Alan Aboudib

Summary: This blog is a summary of the AMA with OpenMined’s NLP team lead and privacy expert Alan Aboudib(link of the video). Alan got his

PrivacyRaven: Comprehensive Privacy Testing for Deep Learning

Summary of Suha S. Hussain’s talk at the OpenMined Privacy Conference 2020.

OpenMined Featured Contributor: November 2020

Interview with Madhava Jay, OpenMined's Featured Contributor for November 2020!

Conference Summary: End-to-end privacy-preserving deep learning on multi-institutional medical imaging data

Speaker: Dr.Georgios Kaisssis, MHBA Video Link: Motivation:AI in medical imaging

Privacy Teaching Series: What is Functional Encryption?

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.

Conference talk summary: Fatemehsadat Mireshghallah - Privacy preserving natural language processing

This blog post summarises Fatemeh's Talk on privacy preserving NLP, showing the threats and mitigations with vulnerabilities in the NLP pipeline.

Notes from OM August Paper Session

The Reviewed Paper: Preserving Differential Privacy in Convolutional Deep Belief Networks (💐Authors: Nhat Hai Phan, Xintao Wu, Dejing Dou)

CKKS explained, Part 5: Rescaling

Fifth part of the series CKKS explained where we see how to define rescaling

Privacy-Preserving Tech - Tools for Safe Data Use

Across research institutions, personal devices, and private companies, humankind is gathering a huge amount of information about ourselves a

Conference Talk Summary: Helen Nissenbaum - Privacy, Contextual Integrity, and Obfuscation

Dr. Helen Nissenbaum is one of the world’s most influential philosophers in the privacy space. She is the author of “Privacy in Context: Tec