Unsupervised Machine Learning for Co/Multimorbidity Analysis

Machine Learning for NLP: Unsupervised learning techniques

• So far we have seen supervised learning (of classification): – learning based on a training set where labelling of instances represents the target (categorisation) function – classifier implements an approximation of the target funtion – outcome: a classification decision • Unsupervised learning: – learning based on unannotated instances; – outcome: a grouping of objects (instances and groups...

Unsupervised Machine Learning

Interactive Algorithms for Unsupervised Machine Learning

This thesis explores the power of interactivity in unsupervised machine learning problems. Interactive algorithms employ feedback driven measurements to mitigate the cost of data acquisition and consequently enable statistical analysis in otherwise intractable settings. Unsupervised learning methods are fundamental tools across a variety of domains, and interactive procedures promise to broaden...

Unsupervised Play: Machine Learning Toolkit for Max

Machine learning models are useful and attractive tools for the interactive computer musician, enabling a breadth of interfaces and instruments. With current consumer hardware it becomes possible to run advanced machine learning algorithms in demanding performance situations, yet expertise remains a prominent entry barrier for most would-be users. Currently available implementations predominant...

Quantum phase recognition via unsupervised machine learning

The application of state-of-the-art machine learning techniques to statistical physic problems has seen a surge of interest for their ability to discriminate phases of matter by extracting essential features in the many-body wavefunction or the ensemble of correlators sampled in Monte Carlo simulations. Here we introduce a generalization of supervised machine learning approaches that allows to ...