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Found 3 papers, 2 papers with code
Tiny Machine Learning for Concept Drift
For the first time in the literature, this paper introduces a Tiny Machine Learning for Concept Drift (TML-CD) solution based on deep learning feature extractors and a k-nearest neighbors classifier integrating a hybrid adaptation module able to deal with concept drift affecting the data-generating process.
A Privacy-Preserving Distributed Architecture for Deep-Learning-as-a-Service
Deep-learning-as-a-service is a novel and promising computing paradigm aiming at providing machine/deep learning solutions and mechanisms through Cloud-based computing infrastructures.
Distributed Deep Convolutional Neural Networks for the Internet-of-Things
Severe constraints on memory and computation characterizing the Internet-of-Things (IoT) units may prevent the execution of Deep Learning (DL)-based solutions, which typically demand large memory and high processing load.
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