3 papers
cs.NE2020
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment
Maryam Parsa, Catherine D. Schuman, Prasanna Date +8
Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms…
cs.LG2019
Exascale Deep Learning to Accelerate Cancer Research
Robert M. Patton, J. Travis Johnston, Steven R. Young +9
Deep learning, through the use of neural networks, has demonstrated remarkable ability to automate many routine tasks when presented with sufficient data for training. The neural n…
cs.CV2013
Gradient Driven Learning for Pooling in Visual Pipeline Feature Extraction Models
Derek Rose, Itamar Arel
Hyper-parameter selection remains a daunting task when building a pattern recognition architecture which performs well, particularly in recently constructed visual pipeline models…