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Cape Privacy (Formerly Dropout Labs)

Privacy & Trust Management for Machine Learning. Operationalize compliance for collaborative machine learning across your organization.

The How and Why of Reversible Tokenization

The How and Why of Reversible Tokenization

When Cape Python first launched it came with a tokenization transformation that allowed users to tokenize their data so they didn’t leak…
Go to the profile of Justin Patriquin
Justin Patriquin
Sep 11, 2020
My Definition of a First-Class Pull Request

My Definition of a First-Class Pull Request

Over the years, I have worked on a few projects where I was the sole developer. Being a sole developer has its challenges since not…
Go to the profile of Devin Schulz
Devin Schulz
Aug 24, 2020
Building Secure Aggregation into TensorFlow Federated

Building Secure Aggregation into TensorFlow Federated

With Morten Dahl and Yann Dupis.
Go to the profile of Jason Mancuso
Jason Mancuso
Aug 20, 2020
Cape Python: Apply Privacy-Enhancing Techniques to Protect Sensitive Data in Pandas and Spark

Cape Python: Apply Privacy-Enhancing Techniques to Protect Sensitive Data in Pandas and Spark

We’re extremely excited to have recently released the Cape Python library. This library is one of the first building blocks to make your…
Go to the profile of Yann Dupis
Yann Dupis
Jul 31, 2020
Privacy-Preserving Machine Learning 2019: A Year in Review

Privacy-Preserving Machine Learning 2019: A Year in Review

Highlighting the top news, research, code, and community events that impacted PPML in 2019.
Go to the profile of Jason Mancuso
Jason Mancuso
Jan 10, 2020
Federated Learning with Secure Aggregation in TensorFlow

Federated Learning with Secure Aggregation in TensorFlow

Integrating TF Encrypted and TensorFlow to
Go to the profile of Justin Patriquin
Justin Patriquin
Dec 18, 2019
Introducing PySyft TensorFlow

Introducing PySyft TensorFlow

We’re excited to announce our contribution of TensorFlow support to OpenMined’s PySyft project!
Go to the profile of Jason Mancuso
Jason Mancuso
Oct 24, 2019
Encrypted Deep Learning Training and Predictions with TF Encrypted Keras

Encrypted Deep Learning Training and Predictions with TF Encrypted Keras

We are super pleased to announce the addition of a Keras compatible API to TF Encrypted!
Go to the profile of Yann Dupis
Yann Dupis
Aug 23, 2019
Bridging Microsoft SEAL into TensorFlow

Bridging Microsoft SEAL into TensorFlow

The road to machine learning with homomorphic encryption
Go to the profile of Justin Patriquin
Justin Patriquin
Aug 8, 2019
A Path to Sub-Second, Encrypted Skin Cancer Detection

A Path to Sub-Second, Encrypted Skin Cancer Detection

How we used TF Encrypted to detect skin cancer using encrypted images in 36 seconds.
Go to the profile of Yann Dupis
Yann Dupis
Jun 13, 2019
Growing TF Encrypted

Growing TF Encrypted

And officially becoming a community project
Go to the profile of Morten Dahl
Morten Dahl
May 17, 2019
Dropout Labs wins the Confidential Computing Challenge!

Dropout Labs wins the Confidential Computing Challenge!

Dropout Labs is very excited to announce that we’ve won the Google Cloud + Intel Confidential Computing Contest!
Go to the profile of Ian Livingstone
Ian Livingstone
May 2, 2019
Secure Logistic Regression: MPC vs Enclave Benchmark

Secure Logistic Regression: MPC vs Enclave Benchmark

With Ben DeCoste.
Go to the profile of Justin Patriquin
Justin Patriquin
Feb 6, 2019
Privacy-Preserving Machine Learning 2018: A Year in Review

Privacy-Preserving Machine Learning 2018: A Year in Review

We highlight the news, research, code, communities, organizations, and economics that made 2018 the breakout year for PPML.
Go to the profile of Jason Mancuso
Jason Mancuso
Jan 10, 2019
Announcing SecureNN in tf-encrypted

Announcing SecureNN in tf-encrypted

We are pleased to announce that our implementation of SecureNN has landed in tf-encrypted!
Go to the profile of Ben DeCoste
Ben DeCoste
Dec 13, 2018
Secret Sharing Explained

Secret Sharing Explained

The primitive behind secure multi-party computation
Go to the profile of Ben DeCoste
Ben DeCoste
Nov 6, 2018
Experimenting with TF Encrypted

Experimenting with TF Encrypted

A Library for Private Machine Learning in TensorFlow
Go to the profile of Morten Dahl
Morten Dahl
Oct 19, 2018
Introducing Dropout Labs

Introducing Dropout Labs

We’re pleased to introduce Dropout Labs, a company focused on secure, privacy-preserving machine learning.
Go to the profile of Gavin Uhma
Gavin Uhma
Oct 19, 2018
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