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Aaron D'Souza

Aaron D'Souza

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    Efficient Learning and Feature Selection in High-Dimensional Regression
    Jo-Anne Ting
    Stefan Schaal
    Neural Computation, vol. 22(4) (2010), pp. 831-886
    Preview
    Bayesian Robot System Identification with Input and Output Noise
    Jo-Anne Ting
    Stefan Schaal
    Neural Networks (2010) (to appear)
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    A Bayesian Approach to Empirical Local Linearization for Robotics
    Jo-Anne Ting
    Sethu Vijayakumar
    Stefan Schaal
    International Conference on Robotics and Automation (ICRA2008)
    Preview
    Automatic outlier detection: A Bayesian approach
    Jo-Anne Ting
    Stefan Schaal
    International Conference on Robotics and Automation (ICRA 2007)
    Preview
    Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
    Jo-Anne Ting
    Kenji Yamamoto
    Toshinori Yoshioka
    Donna Hoffman
    Shinji Kakei
    Lauren Sergio
    John Kalaska
    Mitsuo Kawato
    Peter Strick
    Stefan Schaal
    Advances in Neural Information Processing Systems 18, MIT Press (2006)
    Preview
    Bayesian Regression with Input Noise for High-Dimensional Data
    Jo-Anne Ting
    Stefan Schaal
    In Proceedings of the 23rd International Conference on Machine Learning, ACM Press (2006)
    Preview
    Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
    Jo-Anne Ting
    Kenji Yamamoto
    Toshinori Yoshioka
    Donna L. Hoffman
    Lauren Sergio
    Shinji Kakei
    John Kalaska
    Mitsuo Kawato
    Peter Strick
    Stefan Schaal
    Neural Information Processing Systems (2005)
    The Bayesian backfitting relevance vector machine
    Sethu Vijayakumar
    Stefan Schaal
    International Conference on Machine Learning (2004)