Rapid Development of Compositional AI

no code implementations • 12 Feb 2023 • Lee Martie, Jessie Rosenberg, Veronique Demers, Gaoyuan Zhang, Onkar Bhardwaj, John Henning, Aditya Prasad, Matt Stallone, Ja Young Lee, Lucy Yip, Damilola Adesina, Elahe Paikari, Oscar Resendiz, Sarah Shaw, David Cox

Compositional AI systems, which combine multiple artificial intelligence components together with other application components to solve a larger problem, have no known pattern of development and are often approached in a bespoke and ad hoc style.

Distributed Adversarial Training to Robustify Deep Neural Networks at Scale

1 code implementation • 13 Jun 2022 • Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu

Spurred by that, we propose distributed adversarial training (DAT), a large-batch adversarial training framework implemented over multiple machines.

Distributed Optimization

Reflecting After Learning for Understanding

no code implementations • 18 Oct 2019 • Lee Martie, Mohammad Arif Ul Alam, Gaoyuan Zhang, Ryan R. Anderson

Using the framework on images from ImageNet, we demonstrate systems that unify 41% to 46% of predictions in general and unify 67% to 75% of predictions when the systems can explain their conceptual differences.

General Classification Image Classification