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cs.LG2021
Continual Learning of Generative Models with Limited Data: From Wasserstein-1 Barycenter to Adaptive Coalescence
Mehmet Dedeoglu, Sen Lin, Zhaofeng Zhang +1
Learning generative models is challenging for a network edge node with limited data and computing power. Since tasks in similar environments share model similarity, it is plausible…
cs.LG2020
Accelerating Distributed Online Meta-Learning via Multi-Agent Collaboration under Limited Communication
Sen Lin, Mehmet Dedeoglu, Junshan Zhang
Online meta-learning is emerging as an enabling technique for achieving edge intelligence in the IoT ecosystem. Nevertheless, to learn a good meta-model for within-task fast adapta…