A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
— Machine learning has made great progress during the last decades and is being deployed in a wide range of applications. However, current machine learning techniques are far fro...
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
A common problem in many user studies is gathering natural user behavior unintrusively over a long period of time. We describe a methodology for conducting passive longitudinal st...
This paper presents an agent-based model for decision making, which integrates personal biological and psychological aspects with rational utility-based reasoning. The model takes ...