Tao Sun

According to our database, Tao Sun authored at least 11 papers between 2013 and 2021.

Collaborative distances:

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

2021

REPAINT: Knowledge Transfer in Deep Reinforcement Learning.

Yunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun, Sunil Mallya

Proceedings of the 38th International Conference on Machine Learning, 2021

Gated Transformer for Decoding Human Brain EEG Signals.

Yunzhe Tao, Tao Sun, Aashiq Muhamed, Sahika Genc, Dylan Jackson, Ali Arsanjani, Suri Yaddanapudi, Liang Li, Prachi Kumar

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020

Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks.

Sahika Genc, Sunil Mallya, Sravan Bodapati, Tao Sun, Yunzhe Tao

CoRR, 2020

Robust Multi-Agent Reinforcement Learning with Model Uncertainty.

Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DeepRacer: Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning.

Bharathan Balaji, Sunil Mallya, Sahika Genc, Saurabh Gupta, Leo Dirac, Vineet Khare, Gourav Roy, Tao Sun, Yunzhe Tao, Brian Townsend, Eddie Calleja, Sunil Muralidhara, Dhanasekar Karuppasamy

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning.

Bharathan Balaji, Sunil Mallya, Sahika Genc, Saurabh Gupta, Leo Dirac, Vineet Khare, Gourav Roy, Tao Sun, Yunzhe Tao, Brian Townsend, Eddie Calleja, Sunil Muralidhara, Dhanasekar Karuppasamy

CoRR, 2019

Three-quarter Sibling Regression for Denoising Observational Data.

Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2017

Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models.

Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay, Gerome Miklau

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

A Probabilistic Approach for Learning with Label Proportions Applied to the US Presidential Election.

Tao Sun, Daniel Sheldon, Brendan O'Connor

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2015

Message Passing for Collective Graphical Models.

Tao Sun, Daniel Sheldon, Akshat Kumar

Proceedings of the 32nd International Conference on Machine Learning, 2015

2013

Approximate Inference in Collective Graphical Models.

Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich

Proceedings of the 30th International Conference on Machine Learning, 2013