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MANAS: Multi-Agent Neural Architecture Search
The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a graph-level global objective.
Boundary Optimizing Network (BON)
Given a classification network, we propose to use a collaborative generative network that produces new synthetic data points in the form of perturbations of original data points.
Exploiting Nontrivial Connectivity for Automatic Speech Recognition
Nontrivial connectivity has allowed the training of very deep networks by addressing the problem of vanishing gradients and offering a more efficient method of reusing parameters.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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