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Found 7 papers, 0 papers with code
Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication
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.
Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting
Robots and autonomous agents often complete goal-based tasks with limited resources, relying on imperfect models and sensor measurements.
Dynamic Analysis of Executables to Detect and Characterize Malware
It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life.
Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation
The high dimensionality of hyperspectral imaging forces unique challenges in scope, size and processing requirements.
Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
A detailed circuit and device-level analysis of energy, latency, area, and accuracy are given and compared to relevant designs using standard digital ReRAM and SRAM operations.
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines
Information in neural networks is represented as weighted connections, or synapses, between neurons.
Neurogenesis Deep Learning
Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks.
