ImmuNeCS: Neural Committee Search by an Artificial Immune System

18 Nov 2019 Luc Frachon Wei Pang George M. Coghill

Current Neural Architecture Search techniques can suffer from a few shortcomings, including high computational cost, excessive bias from the search space, conceptual complexity or uncertain empirical benefits over random search. In this paper, we present ImmuNeCS, an attempt at addressing these issues with a method that offers a simple, flexible, and efficient way of building deep learning models automatically, and we demonstrate its effectiveness in the context of convolutional neural networks... (read more)

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Methods used in the Paper

Random Search
Hyperparameter Search
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
Output Functions
Recurrent Neural Networks