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Found 3 papers, 2 papers with code
Accurate and Scalable Image Clustering Based On Sparse Representation of Camera Fingerprint
In this paper, we propose an accurate clustering framework, which exploits linear dependencies among SPNs in their intrinsic vector subspaces.
Training Feedforward Neural Networks with Standard Logistic Activations is Feasible
Training feedforward neural networks with standard logistic activations is considered difficult because of the intrinsic properties of these sigmoidal functions.
Efficient Training for Positive Unlabeled Learning
Positive unlabeled (PU) learning is useful in various practical situations, where there is a need to learn a classifier for a class of interest from an unlabeled data set, which may contain anomalies as well as samples from unknown classes.
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