96 citations · 113 across the 4 of their papers we have counts for
5 papers
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
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…
Device-aware inference operations in SONOS nonvolatile memory arrays
Christopher H. Bennett, T. Patrick Xiao, Ryan Dellana +10
Non-volatile memory arrays can deploy pre-trained neural network models for edge inference. However, these systems are affected by device-level noise and retention issues. Here, we…
Evaluating complexity and resilience trade-offs in emerging memory inference machines
Christopher H. Bennett, Ryan Dellana, T. Patrick Xiao +6
Neuromorphic-style inference only works well if limited hardware resources are maximized properly, e.g. accuracy continues to scale with parameters and complexity in the face of po…
Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication
William Severa, Craig M. Vineyard, Ryan Dellana +2
This paper presents a new technique for training networks for low-precision communication. Targeting minimal communication between nodes not only enables the use of emerging spikin…