Abstract: A system for applications including but not limited to machine learning and unsupervised learning for clustering of data processes an input dataset in a plurality of autoencoders where each autoencoder is configured to produce an indication of a particular structure included in the input dataset and an aggregator combines the indications produced by the plurality of autoencoders based on a weighting vector to produce a weighted combination of the indications that may be used to train the system to create a sparse representation of unlabeled datasets.