13 citations · 38 across the 11 of their papers we have counts for
11 papers
Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing
Klara Nahrstedt, Naresh Shanbhag, Vikram Adve +25
In 2021, the Coordinated Science Laboratory CSL, an Interdisciplinary Research Unit at the University of Illinois Urbana-Champaign, hosted the Future of Computing Symposium to cele…
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks
Hassan Dbouk, Naresh R. Shanbhag
Despite their tremendous successes, convolutional neural networks (CNNs) incur high computational/storage costs and are vulnerable to adversarial perturbations. Recent works on rob…
Robustifying Adversarial Training to the Union of Perturbation Models
Ameya D. Patil, Michael Tuttle, Alexander G. Schwing +1
Classical adversarial training (AT) frameworks are designed to achieve high adversarial accuracy against a single attack type, typically norm-bounded perturbations. R…
Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications
Sujan Kumar Gonugondla, Charbel Sakr, Hassan Dbouk +1
This paper obtains fundamental limits on the computational precision of in-memory computing architectures (IMCs). An IMC noise model and associated SNR metrics are defined and thei…
DBQ: A Differentiable Branch Quantizer for Lightweight Deep Neural Networks
Hassan Dbouk, Hetul Sanghvi, Mahesh Mehendale +1
Deep neural networks have achieved state-of-the art performance on various computer vision tasks. However, their deployment on resource-constrained devices has been hindered due to…
Nanotechnology-inspired Information Processing Systems of the Future
Randy Bryant, Mark Hill, Tom Kazior +9
Nanoscale semiconductor technology has been a key enabler of the computing revolution. It has done so via advances in new materials and manufacturing processes that resulted in the…