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Found 6 papers, 2 papers with code
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection
Encouraged by this inspiring theoretical result on heterogeneous networks, we directly integrate conventional and quadratic neurons in an autoencoder to make a new type of heterogeneous autoencoders.
Manifoldron: Direct Space Partition via Manifold Discovery
A neural network with the widely-used ReLU activation has been shown to partition the sample space into many convex polytopes for prediction.
Storage Fit Learning with Feature Evolvable Streams
Our framework is able to fit its behavior to different storage budgets when learning with feature evolvable streams with unlabeled data.
Prediction with Unpredictable Feature Evolution
Learning with feature evolution studies the scenario where the features of the data streams can evolve, i. e., old features vanish and new features emerge.
Learning with Interpretable Structure from Gated RNN
With the learned FSA and via experiments on artificial and real datasets, we find that FSA is more trustable than the RNN from which it learned, which gives FSA a chance to substitute RNNs in applications involving humans' lives or dangerous facilities.
Learning with Feature Evolvable Streams
To benefit from the recovered features, we develop two ensemble methods.
