Discovery of Hidden Similarity on Collaborative Filtering to Overcome Sparsity Problem. - Sanghack Lee; Jihoon Yang; Sung-Yong Park (Discovery Science, 2004)

A New Polynomial Time Algorithm for Bayesian Network Structure Learning. - Sanghack Lee; Jihoon Yang; Sungyong Park (ADMA, 2006)

m-Transportability: Transportability of a Causal Effect from Multiple Environments. - Sanghack Lee; Vasant G. Honavar (AAAI, 2013)

Learning Classifiers from Distributional Data. - Harris T. Lin; Sanghack Lee; Ngot Bui; Vasant G. Honavar (BigData Congress, 2013)

Transportability from Multiple Environments with Limited Experiments. - Elias Bareinboim; Sanghack Lee; Vasant G. Honavar; Judea Pearl (NIPS, 2013)

Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. - Sanghack Lee; Vasant G. Honavar (UAI, 2013)

Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. - Sanghack Lee; Vasant G. Honavar (ACI@UAI, 2015)

On Learning Causal Models from Relational Data. - Sanghack Lee; Vasant G. Honavar (AAAI, 2016)

A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. - Sanghack Lee; Vasant G. Honavar (UAI, 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 001 (WebSci, 2016)

Self-Discrepancy Conditional Independence Test. - Sanghack Lee; Vasant G. Honavar (UAI, 2017)

Towards Conditional Independence Test for Relational Data. - Sanghack Lee; Vasant G. Honavar (UAI, 2017)

Structural Causal Bandits: Where to Intervene? - Sanghack Lee; Elias Bareinboim (NeurIPS, 2018)

Structural Causal Bandits with Non-Manipulable Variables. - Sanghack Lee; Elias Bareinboim (AAAI, 2019)

General Identifiability with Arbitrary Surrogate Experiments. - Sanghack Lee; Juan D. Correa; Elias Bareinboim (UAI, 2019)

Towards Robust Relational Causal Discovery. - Sanghack Lee; Vasant G. Honavar (UAI, 2019)

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. - Aria Khademi; Sanghack Lee; David Foley; Vasant G. Honavar (WWW, 2019)

Identifiability from a Combination of Observations and Experiments. - Sanghack Lee; Juan D. Correa; Elias Bareinboim (AAAI, 2020)

General Transportability - Synthesizing Observations and Experiments from Heterogeneous Domains. - Sanghack Lee; Juan D. Correa; Elias Bareinboim (AAAI, 2020)

Causal Effect Identifiability under Partial-Observability. - Sanghack Lee; Elias Bareinboim (ICML, 2020)

Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe. - Sanghack Lee; Elias Bareinboim (NeurIPS, 2020)

Nested Counterfactual Identification from Arbitrary Surrogate Experiments. - Juan D. Correa; Sanghack Lee; Elias Bareinboim (NeurIPS, 2021)

Causal Identification with Matrix Equations. - Sanghack Lee; Elias Bareinboim (NeurIPS, 2021)

SNU-Causality Lab @ Causal News Corpus 2022: Detecting Causality by Data Augmentation via Part-of-Speech tagging. - Juhyeon Kim; Yesong Choe; Sanghack Lee (CASE@EMNLP, 2022)

Counterfactual Transportability: A Formal Approach. - Juan D. Correa; Sanghack Lee; Elias Bareinboim (ICML, 2022)

On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition. - Inwoo Hwang; Yunhyeok Kwak; Yeon-Ji Song; Byoung-Tak Zhang; Sanghack Lee (CLeaR, 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)

Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models. - Soheun Yi; Sanghack Lee (AISTATS, 2024)

On Positivity Condition for Causal Inference. - Inwoo Hwang; Yesong Choe; Yeahoon Kwon; Sanghack Lee (ICML, 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 (ICML, 2024)

Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference. - Yonghan Jung; Min Woo Park; Sanghack Lee (NeurIPS, 2024)

Causal Discovery with Deductive Reasoning: One Less Problem. - Jonghwan Kim; Inwoo Hwang; Sanghack Lee (UAI, 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 (UAI, 2024)

Toward a Complete Criterion for Value of Information in Insoluble Decision Problems. - Ryan Carey; Sanghack Lee; Robin J. Evans 002 (Trans. Mach. Learn. Res., 2024)

PEER Pressure: Model-to-Model Regularization for Single Source Domain Generalization. - Dong Kyu Cho; Inwoo Hwang; Sanghack Lee (CVPR, 2025)

Locality-aware Concept Bottleneck Model. - Sujin Jeon; Hyundo Lee; Eungseo Kim; Sanghack Lee; Byoung-Tak Zhang; Inwoo Hwang (CoRR, 2025)