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TROB
2010
159views more  TROB 2010»
13 years 2 months ago
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto
ESA
2009
Springer
94views Algorithms» more  ESA 2009»
14 years 2 months ago
Shape Fitting on Point Sets with Probability Distributions
We consider problems on data sets where each data point has uncertainty described by an individual probability distribution. We develop several frameworks and algorithms for calcul...
Maarten Löffler, Jeff M. Phillips
ESSMAC
2003
Springer
14 years 26 days ago
Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
Daniel Sbarbaro, Roderick Murray-Smith
IJCAI
1989
13 years 8 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
CORR
1998
Springer
98views Education» more  CORR 1998»
13 years 7 months ago
Bayesian Stratified Sampling to Assess Corpus Utility
This paper describes a method for asking statistical questions about a large text corpus. We exemplify the method by addressing the question, "What percentage of Federal Regi...
Judith Hochberg, Clint Scovel, Timothy Thomas, Sam...