Arun Venkatraman

According to our database, Arun Venkatraman authored at least 13 papers between 2014 and 2021.

Collaborative distances:

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

2021

Feedback in Imitation Learning: The Three Regimes of Covariate Shift.

Jonathan C. Spencer, Sanjiban Choudhury, Arun Venkatraman, Brian D. Ziebart, J. Andrew Bagnell

CoRR, 2021

2017

Training Strategies for Time Series: Learning for Prediction, Filtering, and Reinforcement Learning.

Arun Venkatraman

PhD thesis, 2017

Autonomy infused teleoperation with application to brain computer interface controlled manipulation.

Katharina Mülling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey M. Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger, J. Andrew Bagnell

Auton. Robots, 2017

Predictive-State Decoders: Encoding the Future into Recurrent Networks.

Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, James Andrew Bagnell

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction.

Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell

Proceedings of the 34th International Conference on Machine Learning, 2017

Gradient Boosting on Stochastic Data Streams.

Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Improved Learning of Dynamics Models for Control.

Arun Venkatraman, Roberto Capobianco, Lerrel Pinto, Martial Hebert, Daniele Nardi, J. Andrew Bagnell

Proceedings of the International Symposium on Experimental Robotics, 2016

Inference Machines for Nonparametric Filter Learning.

Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew Bagnell

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning to Filter with Predictive State Inference Machines.

Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell

Proceedings of the 33nd International Conference on Machine Learning, 2016

Online Instrumental Variable Regression with Applications to Online Linear System Identification.

Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew Bagnell, Byron Boots

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Autonomy Infused Teleoperation with Application to BCI Manipulation.

Katharina Mülling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey M. Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger, J. Andrew Bagnell

Proceedings of the Robotics: Science and Systems XI, Sapienza University of Rome, 2015

Improving Multi-Step Prediction of Learned Time Series Models.

Arun Venkatraman, Martial Hebert, J. Andrew Bagnell

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Perceiving, learning, and exploiting object affordances for autonomous pile manipulation.

Dov Katz, Arun Venkatraman, Moslem Kazemi, J. Andrew Bagnell, Anthony Stentz

Auton. Robots, 2014