Rather than adversarial minority oversampling, we propose an adversarial oversampling (AO) and a data-space oversampling (DO) approach.
The Latent Space Clustering in Generative adversarial networks (ClusterGAN) method has been successful with high-dimensional data.
While the EC-DT translates the ANN in a layer-wise manner to represent exactly the decision boundaries implicitlylearned by the hidden layers of the network, the Extended C-Net inherits the decompositional approach from EC-DT and combines with a C5 tree learning algorithm to construct the decision rules.
The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning.
The objective of this paper is to test the hypothesis that one can learn from the sequence adopted by the controller some strategies that can act as heuristics in decision support tools for aircraft sequencing.
Trusted autonomy is the scientific and engineering field to establish the foundations and ground work for developing trusted autonomous systems (robotics and software agents) that can be used in our daily life, and can be integrated with humans seamlessly, naturally and efficiently.