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Tag function_approximation [14 articles]

Recent papers classified by the tag function_approximation.
  • The optimal discretization of probability density functions
    Computational Statistics & Data Analysis, Vol. 31, No. 4. (28 October 1999), pp. 475-486.
    by A Christofides, B Tanyi, S Christofides, D Whobrey, N Christofides
    posted to probability function_approximation dynamic_programming discretisation density_estimation by mdreid on 2008-04-30 01:42:46 as ** along with 1 group Statistical Machine Learning
  • Effective Input Variable Selection for Function Approximation
    Artificial Neural Networks – ICANN 2006 (2006), pp. 41-50.
    by L Herrera, H Pomares, I Rojas, M Verleysen, A Guilén
    posted to function_approximation input_selection by Cavadini on 2008-01-17 14:11:56 as ****
  • A Novel Input Stochastic Sensitivity Definition of Radial Basis Function Neural Networks and Its Application to Feature Selection
    Advances in Neural Networks - ISNN 2006 (2006), pp. 1352-1358.
    by Xi-Zhao Wang, Hui Zhang
    posted to function_approximation input_selection by Cavadini on 2008-01-17 14:24:51 as ***
  • Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
    Robotics and Automation, 2007 IEEE International Conference on (2007), pp. 2117-2123.
    by G Petkos, S Vijayakumar
    posted to context function_approximation high_dimensions nonlinear by Cavadini on 2008-04-04 11:36:26 as read
  • A max-piecewise-linear neural network for function approximation
    Neurocomputing, Vol. 71, No. 4-6. (January 2008), pp. 843-852.
    by Chengtao Wen, Xiaoyan Ma
    posted to function_approximation neural_network by Cavadini on 2008-04-03 10:29:47 as read
  • Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
    Neural Processing Letters, Vol. 23, No. 2. (April 2006), pp. 201-228.
    by Chen, Chih-Ming, Lu, Yung-Feng, Hong, Chin-Ming
    posted to function_approximation input_selection neural_network by Cavadini on 2008-01-17 14:28:19 as ***
  • Generalised influential rule search scheme for fuzzy function approximation
    Soft Comput., Vol. 10, No. 8. (June 2006), pp. 631-642.
    by A Chatterjee, A Rakshit, P Siarry
    posted to function_approximation fuzzy by Cavadini on 2008-04-03 10:27:59 as read
  • Incremental Learning Framework for Function Approximation via Combining Mixture of Expert Model and Adaptive Resonance Theory
    Mechatronics and Automation, 2007. ICMA 2007. International Conference on (2007), pp. 3486-3491.
    by Cheoltaek Kim, Ju-Jang Lee
    posted to function_approximation by Cavadini on 2008-04-03 10:32:37 as ****
  • Incremental Online Learning in High Dimensions
    by Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal
    posted to function_approximation input_selection online by Cavadini on 2008-01-17 14:34:44 as ****
  • Learning for the Control of Dynamical Motion Systems
    Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on (2007), pp. 454-459.
    by Pierre-Francois Marteau, Sylvie Gibet
    posted to inverse_dynamics function_approximation control by Cavadini on 2008-06-04 11:21:05 as read
  • Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing)
    (2006)
    by Gregory Shakhnarovich, Trevor Darrell, Piotr Indyk
    posted to function_approximation high_dimensions nonlinear by Cavadini on 2008-04-04 11:27:53 as read
  • Hyper-cubic discretization for TD learning based on autonomous decentralized approach
    Systems, Man and Cybernetics, 2003. IEEE International Conference on, Vol. 4 (2003), pp. 3633-3638 vol.4.
    by Y Kobayashi, S Hosoe
    posted to function_approximation learning reinforcement by Cavadini on 2008-01-15 09:43:41 as ****
  • Backward Varilable Selection of Support Vector Regressors by Block Deletion
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on (2007), pp. 2117-2122.
    by Takashi Nagatani, Shigeo Abe
    posted to function_approximation input_selection by Cavadini on 2008-01-17 14:25:13 as ***
  • Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts
    Artificial Neural Networks – ICANN 2006 (2006), pp. 898-907.
    by Georgios Petkos, Marc Toussaint, Sethu Vijayakumar
    posted to function_approximation high_dimensions by Cavadini on 2008-04-04 11:25:39 as read
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