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Found 5 papers, 2 papers with code
Automatic Infectious Disease Classification Analysis with Concept Discovery
Automatic infectious disease classification from images can facilitate needed medical diagnoses.
Semi-supervised Nonnegative Matrix Factorization for Document Classification
We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators.
Geometry of Linear Convolutional Networks
We study the family of functions that are represented by a linear convolutional neural network (LCN).
Semi-supervised NMF Models for Topic Modeling in Learning Tasks
We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific distributions of uncertainty.
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Stochastic Feedforward Neural Networks: Universal Approximation
We investigate different types of shallow and deep architectures, and the minimal number of layers and units per layer that are sufficient and necessary in order for the network to be able to approximate any given stochastic mapping from the set of inputs to the set of outputs arbitrarily well.
