Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance

no code implementations • 25 Oct 2021 • Jiarong Xing, Leyuan Wang, Shang Zhang, Jack Chen, Ang Chen, Yibo Zhu

Today's auto-tuners (e. g., AutoTVM, Ansor) generate efficient tensor programs by navigating a large search space to identify effective implementations, but they do so with opaque hardware details.

Experimental Demonstration of Learned Time-Domain Digital Back-Propagation

no code implementations • 23 Dec 2019 • Eric Sillekens, Wenting Yi, Daniel Semrau, Alessandro Ottino, Boris Karanov, Sujie Zhou, Kevin Law, Jack Chen, Domanic Lavery, Lidia Galdino, Polina Bayvel, Robert I. Killey

We present the first experimental demonstration of learned time-domain digital back-propagation (DBP), in 64-GBd dual-polarization 64-QAM signal transmission over 1014 km.

Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness

1 code implementation • 7 Jun 2019 • Walt Woods, Jack Chen, Christof Teuscher

For sensitive problems, such as medical imaging or fraud detection, Neural Network (NN) adoption has been slow due to concerns about their reliability, leading to a number of algorithms for explaining their decisions.

Adversarial Defense Fraud Detection +4