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UAI
2000
13 years 9 months ago
Gaussian Process Networks
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
Nir Friedman, Iftach Nachman
SIAMCO
2002
71views more  SIAMCO 2002»
13 years 7 months ago
Rate of Convergence for Constrained Stochastic Approximation Algorithms
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
Robert Buche, Harold J. Kushner
FOSSACS
2005
Springer
14 years 1 months ago
A Computational Model for Multi-variable Differential Calculus
Abstract. We introduce a domain-theoretic computational model for multivariable differential calculus, which for the first time gives rise to data types for differentiable functio...
Abbas Edalat, André Lieutier, Dirk Pattinso...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 2 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...
PG
2002
IEEE
14 years 21 days ago
Approximation with Active B-Spline Curves and Surfaces
An active contour model for parametric curve and surface approximation is presented. The active curve or surface adapts to the model shape to be approximated in an optimization al...
Helmut Pottmann, Stefan Leopoldseder, Michael Hofe...