Nitish Satya Murthy

Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge

2022

Recent years have seen a growing trend of deploying deep neural network-based applications on edge devices. Many of these applications, such as biometric identification, activity tracking, user preference learning, etc., require fine-tuning of the trained …