activity
20142020
most citedMultiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator

184 citations · 301 across the 6 of their papers we have counts for

collaborators
Showing 2017Show all

5 papers · 1 filter

cs.CR2017

Tracking Cyber Adversaries with Adaptive Indicators of Compromise

Justin E. Doak, Joe B. Ingram, Sam A. Mulder +6

A forensics investigation after a breach often uncovers network and host indicators of compromise (IOCs) that can be deployed to sensors to allow early detection of the adversary i…

cs.CR2017

Dynamic Analysis of Executables to Detect and Characterize Malware

Michael R. Smith, Joe B. Ingram, Christopher C. Lamb +4

It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life. We examine the use of machine learning algorithms to d…

cs.NE2017

Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation

William M. Severa, Jerilyn A. Timlin, Suraj Kholwadwala +2

The high dimensionality of hyperspectral imaging forces unique challenges in scope, size and processing requirements. Motivated by the potential for an in-the-field cell sorting de…

cs.AR2017★ 184 cited

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator

Matthew J. Marinella, Sapan Agarwal, Alexander Hsia +6

Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition. Deep networks with >50M parameters are made possible by modern GPU…

q-bio.NC2017

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson +7

Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural network…