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Jo-Anne Ting
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2010 – 2019
- 2017
- [r2]Jo-Anne Ting, Franziska Meier, Sethu Vijayakumar, Stefan Schaal:
Locally Weighted Regression for Control. Encyclopedia of Machine Learning and Data Mining 2017: 759-772 - 2013
- [j4]Wei-Lwun Lu, Jo-Anne Ting, James J. Little, Kevin P. Murphy:
Learning to Track and Identify Players from Broadcast Sports Videos. IEEE Trans. Pattern Anal. Mach. Intell. 35(7): 1704-1716 (2013) - 2011
- [j3]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Bayesian robot system identification with input and output noise. Neural Networks 24(1): 99-108 (2011) - [c12]Wei-Lwun Lu, Jo-Anne Ting, Kevin P. Murphy, James J. Little:
Identifying players in broadcast sports videos using conditional random fields. CVPR 2011: 3249-3256 - [c11]Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting:
Learning attentional policies for tracking and recognition in video with deep networks. ICML 2011: 937-944 - 2010
- [j2]Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
Efficient Learning and Feature Selection in High-Dimensional Regression. Neural Comput. 22(4): 831-886 (2010) - [c10]Hannes P. Saal, Jo-Anne Ting, Sethu Vijayakumar:
Active estimation of object dynamics parameters with tactile sensors. IROS 2010: 916-921 - [c9]Hannes P. Saal, Jo-Anne Ting, Sethu Vijayakumar:
Active Sequential Learning with Tactile Feedback. AISTATS 2010: 677-684 - [r1]Jo-Anne Ting, Sethu Vijayakumar, Stefan Schaal:
Locally Weighted Regression for Control. Encyclopedia of Machine Learning 2010: 613-624
2000 – 2009
- 2008
- [j1]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:
Variational Bayesian least squares: An application to brain-machine interface data. Neural Networks 21(8): 1112-1131 (2008) - [c8]Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
A Bayesian approach to empirical local linearization for robotics. ICRA 2008: 2860-2865 - [c7]Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakumar, Stefan Schaal:
Bayesian Kernel Shaping for Learning Control. NIPS 2008: 1673-1680 - 2007
- [c6]Jo-Anne Ting, Evangelos A. Theodorou, Stefan Schaal:
Learning an Outlier-Robust Kalman Filter. ECML 2007: 748-756 - [c5]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Automatic Outlier Detection: A Bayesian Approach. ICRA 2007: 2489-2494 - [c4]Jo-Anne Ting, Evangelos A. Theodorou, Stefan Schaal:
A Kalman filter for robust outlier detection. IROS 2007: 1514-1519 - 2006
- [c3]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Bayesian regression with input noise for high dimensional data. ICML 2006: 937-944 - [c2]Jo-Anne Ting, Michael N. Mistry, Jan Peters, Stefan Schaal, Jun Nakanishi:
A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics. Robotics: Science and Systems 2006 - 2005
- [c1]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:
Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares. NIPS 2005: 1361-1368
Coauthor Index
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