We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
— This paper describes graph-based relational, unsupervised learning algorithm to infer node replacement graph grammar and its application to metabolic pathways. We search for fr...
Jacek P. Kukluk, Chang Hun You, Lawrence B. Holder...
A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a couple...
Annan Li, Shiguang Shan, Xilin Chen, Xiujuan Chai,...
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...