Multivariate discretization for Bayesian Network structure learning in robot grasping
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Danica Kragic | Carl Henrik Ek | Dan Song | Kai Huebner | D. Kragic | C. Ek | K. Huebner | Dan Song
[1] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[2] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[3] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[4] Katsushi Ikeuchi,et al. Toward automatic robot instruction from perception-mapping human grasps to manipulator grasps , 1997, IEEE Trans. Robotics Autom..
[5] Michael E. Tipping,et al. Probabilistic Principal Component Analysis , 1999 .
[6] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[7] Kilian Q. Weinberger,et al. Learning a kernel matrix for nonlinear dimensionality reduction , 2004, ICML.
[8] Philippe Leray,et al. BNT STRUCTURE LEARNING PACKAGE : Documentation and Experiments , 2004 .
[9] Peter K. Allen,et al. Graspit! A versatile simulator for robotic grasping , 2004, IEEE Robotics & Automation Magazine.
[10] Neil D. Lawrence,et al. Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models , 2005, J. Mach. Learn. Res..
[11] Lawrence D. Fu,et al. A Comparison of Bayesian Network Learning Algorithms from Continuous Data , 2005, AMIA.
[12] Manuel Lopes,et al. Learning Object Affordances: From Sensory--Motor Coordination to Imitation , 2008, IEEE Transactions on Robotics.
[13] Stefan Schaal,et al. Learning and generalization of motor skills by learning from demonstration , 2009, 2009 IEEE International Conference on Robotics and Automation.
[14] K. Dautenhahn,et al. Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions , 2009 .
[15] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[16] I. Ebert‐Uphoff. A Probability-Based Approach to Soft Discretization for Bayesian Networks , 2009 .
[17] Trevor Darrell,et al. Rank priors for continuous non-linear dimensionality reduction , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Hantian Wei. A Novel Multivariate Discretization Method for Mining Association Rules , 2009, 2009 Asia-Pacific Conference on Information Processing.
[19] Michalis K. Titsias,et al. Variational Learning of Inducing Variables in Sparse Gaussian Processes , 2009, AISTATS.
[20] Danica Kragic,et al. Learning task constraints for robot grasping using graphical models , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[21] Danica Kragic,et al. Integrating grasp planning with online stability assessment using tactile sensing , 2011, 2011 IEEE International Conference on Robotics and Automation.
[22] Kai Huebner. BADGr - A toolbox for box-based approximation, decomposition and GRasping , 2012, Robotics Auton. Syst..
[23] Michael C. Hout,et al. Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.