Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge

Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge

We consider a resource-constrained Edge Device (ED), such as an IoT sensor or a microcontroller unit, embedded with a small-size ML model (S-ML) for a generic classification application and an Edge Server (ES) that hosts a large-size ML model (L-ML). Since the inference accuracy of S-ML is lower tha...

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Bibliographic Details
Main Authors: Vishnu Narayanan Moothedath, Jaya Prakash Champati, James Gross
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Hierarchical inference
edge computing
regret bound
continuous experts
Online Access:https://ieeexplore.ieee.org/document/10436693/
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