Qitong Gao

According to our database, Qitong Gao authored at least 15 papers between 2019 and 2024.

Collaborative distances:

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

2024

ε-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment.

Hao-Lun Hsu, Qitong Gao, Miroslav Pajic

CoRR, 2024

2023

Robust Reinforcement Learning through Efficient Adversarial Herding.

Juncheng Dong, Hao-Lun Hsu, Qitong Gao, Vahid Tarokh, Miroslav Pajic

CoRR, 2023

Off-Policy Evaluation for Human Feedback.

Qitong Gao, Ge Gao, Juncheng Dong, Vahid Tarokh, Min Chi, Miroslav Pajic

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Variational Latent Branching Model for Off-Policy Evaluation.

Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment.

Qitong Gao, Stephen L. Schmidt, Afsana Chowdhury, Guangyu Feng, Jennifer J. Peters, Katherine Genty, Warren M. Grill, Dennis A. Turner, Miroslav Pajic

Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems, 2023

2022

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification.

Ge Gao, Qitong Gao, Xi Yang, Miroslav Pajic, Min Chi

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Gradient Importance Learning for Incomplete Observations.

Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning-Based Vulnerability Analysis of Cyber-Physical Systems.

Amir Khazraei, Spencer Hallyburton, Qitong Gao, Yu Wang, Miroslav Pajic

Proceedings of the 13th ACM/IEEE International Conference on Cyber-Physical Systems, 2022

Offline Policy Evaluation for Learning-based Deep Brain Stimulation Controllers.

Qitong Gao, Stephen L. Schmidt, Karthik Kamaravelu, Dennis A. Turner, Warren M. Grill, Miroslav Pajic

Proceedings of the 13th ACM/IEEE International Conference on Cyber-Physical Systems, 2022

Learning Monotone Dynamics by Neural Networks.

Yu Wang, Qitong Gao, Miroslav Pajic

Proceedings of the American Control Conference, 2022

2021

Imputation-Free Learning from Incomplete Observations.

Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

CoRR, 2021

2020

Deep Learning for Stable Monotone Dynamical Systems.

Yu Wang, Qitong Gao, Miroslav Pajic

CoRR, 2020

Deep Imitative Reinforcement Learning for Temporal Logic Robot Motion Planning with Noisy Semantic Observations.

Qitong Gao, Miroslav Pajic, Michael M. Zavlanos

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

Model-Based Design of Closed Loop Deep Brain Stimulation Controller using Reinforcement Learning.

Qitong Gao, Michael Naumann, Ilija Jovanov, Vuk Lesi, Karthik Kumaravelu, Warren M. Grill, Miroslav Pajic

Proceedings of the 11th ACM/IEEE International Conference on Cyber-Physical Systems, 2020

2019

Reduced variance deep reinforcement learning with temporal logic specifications.

Qitong Gao, Davood Hajinezhad, Yan Zhang, Yiannis Kantaros, Michael M. Zavlanos

Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, 2019