Aaron D'Souza

Google Publications

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    Bayesian Robot System Identification with Input and Output Noise

    Jo-Anne Ting, Aaron D'Souza, Stefan Schaal

    Neural Networks (2010) (to appear)

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    Efficient Learning and Feature Selection in High-Dimensional Regression

    Jo-Anne Ting, Aaron D'Souza, Stefan Schaal

    Neural Computation, vol. 22(4) (2010), pp. 831-886

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    A Bayesian Approach to Empirical Local Linearization for Robotics

    Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal

    International Conference on Robotics and Automation (ICRA2008)

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    Automatic outlier detection: A Bayesian approach

    Jo-Anne Ting, Aaron D'Souza, Stefan Schaal

    International Conference on Robotics and Automation (ICRA 2007)

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    Bayesian Regression with Input Noise for High-Dimensional Data

    Jo-Anne Ting, Aaron D'Souza, Stefan Schaal

    In Proceedings of the 23rd International Conference on Machine Learning, ACM Press (2006)

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    Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares

    Jo-Anne Ting, Aaron D'Souza, 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)

Previous Publications

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    Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares

    Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka, Donna L. Hoffman, Lauren Sergio, Shinji Kakei, John Kalaska, Mitsuo Kawato, Peter Strick, Stefan Schaal

    Neural Information Processing Systems (2005)

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    The Bayesian backfitting relevance vector machine

    Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal

    International Conference on Machine Learning (2004)