This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
This paper addresses the training of classification trees for weakly labelled data. We call ”weakly labelled data”, a training set such as the prior labelling information pro...
An algorithm has been developed to automatically construct individual models of normal activity within a home using motion sensor data. Alerts can be generated when a period of in...
Paul Cuddihy, Jenny Weisenberg, Catherine Graichen...
Most traffic management and optimization tasks, such as accident detection or optimal vehicle routing, require an ability to adequately model, reason about and predict irregular an...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...