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IJAR
2008
119views more  IJAR 2008»
13 years 10 months ago
Adapting Bayes network structures to non-stationary domains
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Søren Holbech Nielsen, Thomas D. Nielsen
PAMI
2008
182views more  PAMI 2008»
13 years 10 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
CHI
2011
ACM
13 years 1 months ago
GreenHat: exploring the natural environment through experts' perspectives
We present GreenHat, an interactive mobile learning application that helps students learn about biodiversity and sustainability issues in their surroundings from experts’ points...
Kimiko Ryokai, Lora Oehlberg, Michael Manoochehri,...
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
14 years 3 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
IVC
2010
128views more  IVC 2010»
13 years 8 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis