Machine Learning

At the core of much of our research is machine learning (ML) for predicting, classifying and fusing multiple neural and non-neural data streams to better identify the cortical and subcortical networks underlying rapid decision making. Our methods employ a number of recent advances in ML, including sparse feature spaces, kernel machines, deep learing and transductive learning.