4 citations · 7 across the 2 of their papers we have counts for
3 papers
TACOS: Task Agnostic Continual Learning in Spiking Neural Networks
Nicholas Soures, Peter Helfer, Anurag Daram +2
Catastrophic interference, the loss of previously learned information when learning new information, remains a major challenge in machine learning. Since living organisms do not se…
TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT
Hamed F. Langroudi, Vedant Karia, Tej Pandit +1
In this research, we propose a new low-precision framework, TENT, to leverage the benefits of a tapered fixed-point numerical format in TinyML models. We introduce a tapered fixed-…
Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit
Seyed H. F. Langroudi, Tej Pandit, Dhireesha Kudithipudi
Performing the inference step of deep learning in resource constrained environments, such as embedded devices, is challenging. Success requires optimization at both software and ha…