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Communication-Efficient Separable Neural Network for Distributed Inference on Edge Devices
The inference of Neural Networks is usually restricted by the resources (e. g., computing power, memory, bandwidth) on edge devices.
Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation
While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated.
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