Junzhe Zhang

According to our database, Junzhe Zhang authored at least 18 papers between 2017 and 2024.

Collaborative distances:

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

2024

Causally Aligned Curriculum Learning.

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Safe Policy Learning under Partial Identifiability: A Causal Approach.

Shalmali Joshi, Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Scores for Learning Discrete Causal Graphs with Unobserved Confounders.

Alexis Bellot, Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Causal Imitation Learning via Inverse Reinforcement Learning.

Kangrui Ruan, Junzhe Zhang, Xuan Di, Elias Bareinboim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Online Reinforcement Learning for Mixed Policy Scopes.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Partial Counterfactual Identification from Observational and Experimental Data.

Junzhe Zhang, Jin Tian, Elias Bareinboim

Proceedings of the International Conference on Machine Learning, 2022

Can Humans Be out of the Loop?

Junzhe Zhang, Elias Bareinboim

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Sequential Causal Imitation Learning with Unobserved Confounders.

Daniel Kumor, Junzhe Zhang, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bounding Causal Effects on Continuous Outcome.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Causal Imitation Learning With Unobserved Confounders.

Junzhe Zhang, Daniel Kumor, Elias Bareinboim

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

Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach.

Junzhe Zhang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Non-Parametric Path Analysis in Structural Causal Models.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Equality of Opportunity in Classification: A Causal Approach.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Characterizing the Limits of Autonomous Systems.

Junzhe Zhang, Elias Bareinboim

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Fairness in Decision-Making - The Causal Explanation Formula.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Transfer Learning in Multi-Armed Bandits: A Causal Approach.

Junzhe Zhang, Elias Bareinboim

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Transfer Learning in Multi-Armed Bandit: A Causal Approach.

Junzhe Zhang, Elias Bareinboim

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017