Jo-Anne Ting

According to our database, Jo-Anne Ting authored at least 18 papers between 2005 and 2017.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2017

Locally Weighted Regression for Control.

Jo-Anne Ting, Franziska Meier, Sethu Vijayakumar, Stefan Schaal

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

2013

Learning to Track and Identify Players from Broadcast Sports Videos.

Wei-Lwun Lu, Jo-Anne Ting, James J. Little, Kevin P. Murphy

IEEE Trans. Pattern Anal. Mach. Intell., 2013

2011

Bayesian robot system identification with input and output noise.

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

Neural Networks, 2011

Learning attentional policies for tracking and recognition in video with deep networks.

Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting

Proceedings of the 28th International Conference on Machine Learning, 2011

Identifying players in broadcast sports videos using conditional random fields.

Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Locally Weighted Regression for Control.

Jo-Anne Ting, Sethu Vijayakumar, Stefan Schaal

Proceedings of the Encyclopedia of Machine Learning, 2010

Efficient Learning and Feature Selection in High-Dimensional Regression.

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

Neural Comput., 2010

Active Sequential Learning with Tactile Feedback.

Hannes P. Saal, Jo-Anne Ting, Sethu Vijayakumar

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Active estimation of object dynamics parameters with tactile sensors.

Hannes P. Saal, Jo-Anne Ting, Sethu Vijayakumar

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

2008

Variational Bayesian least squares: An application to brain-machine interface data.

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

Neural Networks, 2008

Bayesian Kernel Shaping for Learning Control.

Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakumar, Stefan Schaal

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

A Bayesian approach to empirical local linearization for robotics.

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

Proceedings of the 2008 IEEE International Conference on Robotics and Automation, 2008

2007

A Kalman filter for robust outlier detection.

Jo-Anne Ting, Evangelos A. Theodorou, Stefan Schaal

Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29, 2007

Automatic Outlier Detection: A Bayesian Approach.

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

Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 2007

Learning an Outlier-Robust Kalman Filter.

Jo-Anne Ting, Evangelos A. Theodorou, Stefan Schaal

Proceedings of the Machine Learning: ECML 2007, 2007

2006

A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics.

Jo-Anne Ting, Michael N. Mistry, Jan Peters, Stefan Schaal, Jun Nakanishi

Proceedings of the Robotics: Science and Systems II, 2006

Bayesian regression with input noise for high dimensional data.

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

Proceedings of the Machine Learning, 2006

2005

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

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005