In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassificati...
Abstract—Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a dete...
—Continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. By solving the manybody Schr¨odinge...
Kenneth Esler, Jeongnim Kim, David M. Ceperley, Lu...