Training a Neural Network Using Small Training Datasets

摘要

Training datasets are determined for training neural networks. An input dataset comprising a plurality of samples is provided as training dataset to the neural network. Vector representations of samples of the input dataset are obtained from a hidden layer of the neural network. The samples are clustered using the vector representation. The samples are scored based on a metric that indicates the similarity of the sample to its cluster. A subset of samples is determined by excluding samples that have high similarity with their clusters. The subset of samples is labelled and used for training the neural network.