‘P-Meta’ Learning Approach Boosts Data and Memory Efficiency for On-Device DNN Adaptation in the IoT | Synced
In the new paper p-Meta: Towards On-device Deep Model Adaptation, a research team from ETH Zurich, Singapore Management University and Beihang University proposes p-Meta, a novel meta-learning meth...
Source: Synced | AI Technology & Industry Review
In the new paper p-Meta: Towards On-device Deep Model Adaptation, a research team from ETH Zurich, Singapore Management University and Beihang University proposes p-Meta, a novel meta-learning method for data- and memory-efficient on-device adaption of deep neural networks for IoT applications.