Aaron D'Souza

Google Publications

Bayesian Robot System Identification with Input and Output Noise

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

Neural Networks (2010) (to appear)
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
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)
Automatic outlier detection: A Bayesian approach

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

International Conference on Robotics and Automation (ICRA 2007)
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)
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)

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)
The Bayesian backfitting relevance vector machine

Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal

International Conference on Machine Learning (2004)