Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow Despite the success of supervised machine learning and ...

The team proposed a novel representation learning method based on an integrated autoencoders for unsupervised domain adaptation. A sparse autoencoder is introduced to combine the inter- and inner ...

Learning without feedback: Neuroscientist helps uncover the influence of unsupervised learning on humans and machines by Daniel Fleiter, Max Planck Society Editors' notes ...

We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses ...

Unsupervised, a company developing a platform that leverages self-supervised machine learning to spot trends, raised $35 million.