Sanghack Lee

According to our database, Sanghack Lee authored at least 31 papers between 2004 and 2024.

Collaborative distances:

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

2024

Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction.

Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang

CoRR, 2024

Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning.

Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi, Byoung-Tak Zhang, Sanghack Lee

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On Positivity Condition for Causal Inference.

Inwoo Hwang, Yesong Choe, Yeahoon Kwon, Sanghack Lee

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models.

Soheun Yi, Sanghack Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?

Chanhui Lee, Juhyeon Kim, Yongjun Jeong, Juhyun Lyu, Junghee Kim, Sangmin Lee, Sangjun Han, Hyeokjun Choe, Soyeon Park, Woohyung Lim, Sungbin Lim, Sanghack Lee

CoRR, 2023

On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition.

Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang, Sanghack Lee

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Counterfactual Transportability: A Formal Approach.

Juan D. Correa, Sanghack Lee, Elias Bareinboim

Proceedings of the International Conference on Machine Learning, 2022

SNU-Causality Lab @ Causal News Corpus 2022: Detecting Causality by Data Augmentation via Part-of-Speech tagging.

Juhyeon Kim, Yesong Choe, Sanghack Lee

Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, 2022

2021

Causal Identification with Matrix Equations.

Sanghack Lee, Elias Bareinboim

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

Nested Counterfactual Identification from Arbitrary Surrogate Experiments.

Juan D. Correa, Sanghack Lee, Elias Bareinboim

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

2020

Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe.

Sanghack Lee, Elias Bareinboim

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

Causal Effect Identifiability under Partial-Observability.

Sanghack Lee, Elias Bareinboim

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

General Transportability - Synthesizing Observations and Experiments from Heterogeneous Domains.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Identifiability from a Combination of Observations and Experiments.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality.

Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar

Proceedings of the World Wide Web Conference, 2019

Towards Robust Relational Causal Discovery.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

General Identifiability with Arbitrary Surrogate Experiments.

Sanghack Lee, Juan D. Correa, Elias Bareinboim

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Structural Causal Bandits with Non-Manipulable Variables.

Sanghack Lee, Elias Bareinboim

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Structural Causal Bandits: Where to Intervene?

Sanghack Lee, Elias Bareinboim

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

2017

Towards Conditional Independence Test for Relational Data.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Self-Discrepancy Conditional Independence Test.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2016

Teens are from mars, adults are from venus: analyzing and predicting age groups with behavioral characteristics in instagram.

Kyungsik Han, Sanghack Lee, Jin Yea Jang, Yong Jung, Dongwon Lee

Proceedings of the 8th ACM Conference on Web Science, 2016

A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

On Learning Causal Models from Relational Data.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning.

Sanghack Lee, Vasant G. Honavar

Proceedings of the UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 2015

2013

Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Transportability from Multiple Environments with Limited Experiments.

Elias Bareinboim, Sanghack Lee, Vasant G. Honavar, Judea Pearl

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Learning Classifiers from Distributional Data.

Harris T. Lin, Sanghack Lee, Ngot Bui, Vasant G. Honavar

Proceedings of the IEEE International Congress on Big Data, 2013

m-Transportability: Transportability of a Causal Effect from Multiple Environments.

Sanghack Lee, Vasant G. Honavar

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2006

A New Polynomial Time Algorithm for Bayesian Network Structure Learning.

Sanghack Lee, Jihoon Yang, Sungyong Park

Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006

2004

Discovery of Hidden Similarity on Collaborative Filtering to Overcome Sparsity Problem.

Sanghack Lee, Jihoon Yang, Sung-Yong Park

Proceedings of the Discovery Science, 7th International Conference, 2004