184 citations · 301 across the 6 of their papers we have counts for
8 papers
Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication
Ojas Parekh, Cynthia A. Phillips, Conrad D. James +1
Boolean circuits of McCulloch-Pitts threshold gates are a classic model of neural computation studied heavily in the late 20th century as a model of general computation. Recent adv…
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…
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…
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…
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…
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…