We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
: New information and computing technologies offer cost efficient and effective learning opportunities for health care professionals. The Assisted Electronic Communication project ...
Peter Scott, Fiona Brooks, Kevin Quick, Maria Maci...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Microarchitectural prediction based on neural learning has received increasing attention in recent years. However, neural prediction remains impractical because its superior accur...