Resource-Efficient Neural Networks for Embedded Systems

arXiv:2001.03048v3 Announce Type: replace-cross
Abstract: While machine learning is traditionally a resource intensive task, embedded systems, autonomous navigation, and the vision of the Internet of Things fuel the interest in resource-efficient approaches. These approaches aim for a carefully chosen trade-off between performance and resource consumption in terms of computation and energy. The development of such approaches is among the major challenges in current machine learning research and key to ensure a smooth transition of machine learning technology from a scientific …

abstract aim arxiv autonomous computation consumption cs.lg development embedded energy internet internet of things machine machine learning navigation networks neural networks performance stat.ml systems terms trade trade-off type vision