Unsupervised machine learning technique for classifying production zones in unconventional reservoirs

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

Classifying Dynamic Objects: An Unsupervised Learning Approach

For robots operating in real-world environments, the ability to deal with dynamic entities such as humans, animals, vehicles, or other robots is of fundamental importance. The variability of dynamic objects, however, is large in general, which makes it hard to manually design suitable models for their appearance and dynamics. In this paper, we present an unsupervised learning approach to this m...

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...