activity
20162018
most citedTensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

9.7k citations · 16.6k across the 8 of their papers we have counts for

collaborators
Showing 2016Show all

5 papers · 1 filter

cs.CL2016★ 36 cited

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…

cs.CR2016★ 119 cited

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…

stat.ML2016★ 185 cited

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…

stat.ML2016★ 6.3k cited

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…

cs.DC2016★ 9.7k cited

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…