This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
— We present a novel approach for determining robot movements that efficiently accomplish the robot’s tasks while not hindering the movements of people within the environment....
Brian Ziebart, Nathan D. Ratliff, Garratt Gallaghe...
Enabling virtual agents to quickly and accurately infer users’ psychological characteristics such as their personality could support a broad range of applications in education, t...
Jennifer L. Robison, Jonathan P. Rowe, Scott W. Mc...
: Many diseases, especially solid tumors, involve the disruption or deregulation of cellular processes. Most current work using gene expression and other high-throughput data, simp...