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    IROS
    2009
    IEEE
    155views Robotics» more  IROS 2009»
    Active learning using mean shift optimization for robot grasping
    14 years 2 months ago
    Active learning using mean shift optimization for robot grasping
    Download  www.kyb.tuebingen.mpg.de
    — When children learn to grasp a new object, they often know several possible grasping points from observing a parent’s demonstration and subsequently learn better grasps by tr...
    Oliver Kroemer, Renaud Detry, Justus H. Piater, Ja...
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    WSC
    2007
    166views Modeling And Simulation» more  WSC 2007»
    Optimizing time warp simulation with reinforcement learning techniques
    13 years 10 months ago
    Optimizing time warp simulation with reinforcement learning techniques
    Download  www.informs-sim.org
    Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
    Jun Wang, Carl Tropper
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    VIS
    2007
    IEEE
    199views Visualization» more  VIS 2007»
    Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles
    14 years 8 months ago
    Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles
    Download  www.cs.utah.edu
    Abstract-This paper describes a method for constructing isosurface triangulations of sampled, volumetric, three-dimensional scalar fields. The resulting meshes consist of triangles...
    Miriah Meyer, Robert M. Kirby, Ross Whitaker
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    EUSFLAT
    2003
    121views Fuzzy Logic» more  EUSFLAT 2003»
    An adaptive learning algorithm for a neo fuzzy neuron
    13 years 9 months ago
    An adaptive learning algorithm for a neo fuzzy neuron
    Download  www.eusflat.org
    In the paper, a new optimal learning algorithm for a neo-fuzzy neuron (NFN) is proposed. The algorithm is characteristic in that it provides online tuning of not only the synaptic...
    Yevgeniy Bodyanskiy, Illya Kokshenev, Vitaliy Kolo...
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    IJON
    2007
    118views more  IJON 2007»
    Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
    13 years 7 months ago
    Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
    Download  web.mst.edu
    To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
    Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...
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