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[D] private computing in tensorflow

we are hosting a live session with the author of the paper “private computing in tensorflow” at lunch time EST. See more details here: https://www.eventbrite.ca/e/private-machine-learning-in-tensorflow-aisc-lunch-learn-tickets-64991077061

what questions do you have about this paper that we can ask the author?

abstract: We present a framework for experimenting with secure multi-party computation directly in TensorFlow. By doing so we benefit from several properties valuable to both researchers and practitioners, including tight integration with ordinary machine learning processes, existing optimizations for distributed computation in TensorFlow, high-level abstractions for expressing complex algorithms and protocols, and an expanded set of familiar tooling. We give an open source implementation of a state-of-the-art protocol and report on concrete benchmarks using typical models from private machine learning.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.