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ICML
2006
IEEE
14 years 8 months ago
Hidden process models
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...
BIOCOMP
2007
13 years 9 months ago
Learning Node Replacement Graph Grammars in Metabolic Pathways
— 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...
AIED
2005
Springer
14 years 1 months ago
Inferring learning and attitudes from a Bayesian Network of log file data
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...
Ivon Arroyo, Beverly Park Woolf
FGR
2008
IEEE
304views Biometrics» more  FGR 2008»
14 years 1 months ago
Recovering 3D facial shape via coupled 2D/3D space learning
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,...
IJCNN
2000
IEEE
13 years 12 months ago
On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application
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...
Eiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio