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» Learning Nonlinear Dynamical Systems Using an EM Algorithm
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ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
15 years 4 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
ICIC
2005
Springer
15 years 3 months ago
Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
PPCP
1993
15 years 1 months ago
Practical Issues in Graphical Constraints
Use of constraint-based techniques in interactive graphics applications poses a variety of unique challenges to system implementors. This paper begins by describing how interface ...
Michael Gleicher
GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
15 years 3 months ago
Mining breast cancer data with XCS
In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a prima...
Faten Kharbat, Larry Bull, Mohammed Odeh
RECSYS
2009
ACM
15 years 4 months ago
FeedbackTrust: using feedback effects in trust-based recommendation systems
With the advent of online social networks, the trust-based approach to recommendation has emerged which exploits the trust network among users and makes recommendations based on t...
Samaneh Moghaddam, Mohsen Jamali, Martin Ester, Ja...