9.7k citations · 16.6k across the 8 of their papers we have counts for
8 papers
Dynamic Control Flow in Large-Scale Machine Learning
Yuan Yu, Martín Abadi, Paul Barham +12
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcem…
Adversarial Patch
Tom B. Brown, Dandelion Mané, Aurko Roy +2
We present a method to create universal, robust, targeted adversarial image patches in the real world. The patches are universal because they can be used to attack any scene, robus…
On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches
Martín Abadi, Úlfar Erlingsson, Ian Goodfellow +5
The recent, remarkable growth of machine learning has led to intense interest in the privacy of the data on which machine learning relies, and to new techniques for preserving priv…
Learning a Natural Language Interface with Neural Programmer
Arvind Neelakantan, Quoc V. Le, Martin Abadi +2
Learning a natural language interface for database tables is a challenging task that involves deep language understanding and multi-step reasoning. The task is often approached by…
Learning to Protect Communications with Adversarial Neural Cryptography
Martín Abadi, David G. Andersen
We ask whether neural networks can learn to use secret keys to protect information from other neural networks. Specifically, we focus on ensuring confidentiality properties in a mu…
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Nicolas Papernot, Martín Abadi, Úlfar Erlingsson +2
Some machine learning applications involve training data that is sensitive, such as the medical histories of patients in a clinical trial. A model may inadvertently and implicitly…
Deep Learning with Differential Privacy
Martín Abadi, Andy Chu, Ian Goodfellow +4
Machine learning techniques based on neural networks are achieving remarkable results in a wide variety of domains. Often, the training of models requires large, representative dat…
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi, Ashish Agarwal, Paul Barham +37
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…