Sanghack Lee - RankMe

52 papers A* 18A 9B 1C 1Journal 17Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Mitigating Length Bias in RLHF Through a Causal Lens. AAAI Hyeonji Kim, Sujeong Oh, Sanghack Lee
2025	J	`jnl`	Locality-aware Concept Bottleneck Model. CoRR Sujin Jeon, Hyundo Lee, Eungseo Kim, Sanghack Lee, Byoung-Tak Zhang, Inwoo Hwang
2025	J	`jnl`	Mitigating Length Bias in RLHF through a Causal Lens. CoRR Hyeonji Kim, Sujeong Oh, Sanghack Lee
2025	J	`jnl`	On Incorporating Prior Knowledge Extracted From Large Language Models Into Causal Discovery. IEEE Access Chanhui Lee, Juhyeon Kim, Yongjun Jeong, Yoonseok Yeom, Juhyun Lyu, Junghee Kim, Sangmin Lee, Sangjun Han, Hyeokjun Choe, Soyeon Park, Woohyung Lim, Sungbin Lim, Sanghack Lee
2025	A*	`conf`	On Predicting Post-Click Conversion Rate via Counterfactual Inference. ICDM Junhyung Ahn, Sanghack Lee
2025	J	`jnl`	On Predicting Post-Click Conversion Rate via Counterfactual Inference. CoRR Junhyung Ahn, Sanghack Lee
2025	J	`jnl`	On Transportability for Structural Causal Bandits. CoRR Min Woo Park, Sanghack Lee
2025	A*	`conf`	PEER Pressure: Model-to-Model Regularization for Single Source Domain Generalization. CVPR Dong Kyu Cho, Inwoo Hwang, Sanghack Lee
2025	J	`jnl`	PEER pressure: Model-to-Model Regularization for Single Source Domain Generalization. CoRR Dong Kyu Cho, Inwoo Hwang, Sanghack Lee
2025	J	`jnl`	Towards Causal Representation Learning with Observable Sources as Auxiliaries. CoRR Kwonho Kim, Heejeong Nam, Inwoo Hwang, Sanghack Lee
2024	A	`conf`	Causal Discovery with Deductive Reasoning: One Less Problem. UAI Jonghwan Kim, Inwoo Hwang, Sanghack Lee
2024	A*	`conf`	Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference. NeurIPS Yonghan Jung, Min Woo Park, Sanghack Lee
2024	A	`conf`	Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction. UAI Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang
2024	J	`jnl`	Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction. CoRR Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang
2024	A	`conf`	Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models. AISTATS Soheun Yi, Sanghack Lee
2024	A*	`conf`	Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning. ICML Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi, Byoung-Tak Zhang, Sanghack Lee
2024	J	`jnl`	Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning. CoRR Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi, Byoung-Tak Zhang, Sanghack Lee
2024	J	`jnl`	On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition. CoRR Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang, Sanghack Lee
2024	A*	`conf`	On Positivity Condition for Causal Inference. ICML Inwoo Hwang, Yesong Choe, Yeahoon Kwon, Sanghack Lee
2024	J	`jnl`	Toward a Complete Criterion for Value of Information in Insoluble Decision Problems. Trans. Mach. Learn. Res. Ryan Carey, Sanghack Lee, Robin J. Evans
2023	J	`jnl`	Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms? CoRR Chanhui Lee, Juhyeon Kim, Yongjun Jeong, Juhyun Lyu, Junghee Kim, Sangmin Lee, Sangjun Han, Hyeokjun Choe, Soyeon Park, Woohyung Lim, Sungbin Lim, Sanghack Lee
2023	—	`conf`	On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition. CLeaR Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang, Sanghack Lee
2022	A*	`conf`	Counterfactual Transportability: A Formal Approach. ICML Juan D. Correa, Sanghack Lee, Elias Bareinboim
2022	—	`conf`	SNU-Causality Lab @ Causal News Corpus 2022: Detecting Causality by Data Augmentation via Part-of-Speech tagging. CASE@EMNLP Juhyeon Kim, Yesong Choe, Sanghack Lee
2021	A*	`conf`	Causal Identification with Matrix Equations. NeurIPS Sanghack Lee, Elias Bareinboim
2021	A*	`conf`	Nested Counterfactual Identification from Arbitrary Surrogate Experiments. NeurIPS Juan D. Correa, Sanghack Lee, Elias Bareinboim
2021	J	`jnl`	Nested Counterfactual Identification from Arbitrary Surrogate Experiments. CoRR Juan D. Correa, Sanghack Lee, Elias Bareinboim
2020	A*	`conf`	Causal Effect Identifiability under Partial-Observability. ICML Sanghack Lee, Elias Bareinboim
2020	A*	`conf`	Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe. NeurIPS Sanghack Lee, Elias Bareinboim
2020	A*	`conf`	General Transportability - Synthesizing Observations and Experiments from Heterogeneous Domains. AAAI Sanghack Lee, Juan D. Correa, Elias Bareinboim
2020	A*	`conf`	Identifiability from a Combination of Observations and Experiments. AAAI Sanghack Lee, Juan D. Correa, Elias Bareinboim
2019	A*	`conf`	Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. WWW Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar
2019	J	`jnl`	Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. CoRR Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar
2019	A	`conf`	General Identifiability with Arbitrary Surrogate Experiments. UAI Sanghack Lee, Juan D. Correa, Elias Bareinboim
2019	A*	`conf`	Structural Causal Bandits with Non-Manipulable Variables. AAAI Sanghack Lee, Elias Bareinboim
2019	A	`conf`	Towards Robust Relational Causal Discovery. UAI Sanghack Lee, Vasant G. Honavar
2019	J	`jnl`	Towards Robust Relational Causal Discovery. CoRR Sanghack Lee, Vasant G. Honavar
2018	A*	`conf`	Structural Causal Bandits: Where to Intervene? NeurIPS Sanghack Lee, Elias Bareinboim
2017	A	`conf`	Self-Discrepancy Conditional Independence Test. UAI Sanghack Lee, Vasant G. Honavar
2017	A	`conf`	Towards Conditional Independence Test for Relational Data. UAI Sanghack Lee, Vasant G. Honavar
2016	A	`conf`	A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. UAI Sanghack Lee, Vasant G. Honavar
2016	A*	`conf`	On Learning Causal Models from Relational Data. AAAI Sanghack Lee, Vasant G. Honavar
2016	—	`conf`	Teens are from mars, adults are from venus: analyzing and predicting age groups with behavioral characteristics in instagram. WebSci Kyungsik Han, Sanghack Lee, Jin Yea Jang, Yong Jung, Dongwon Lee
2015	—	`conf`	Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. ACI@UAI Sanghack Lee, Vasant G. Honavar
2015	J	`jnl`	Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. CoRR Sanghack Lee, Vasant G. Honavar
2013	A	`conf`	Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. UAI Sanghack Lee, Vasant G. Honavar
2013	J	`jnl`	Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. CoRR Sanghack Lee, Vasant G. Honavar
2013	—	`conf`	Learning Classifiers from Distributional Data. BigData Congress Harris T. Lin, Sanghack Lee, Ngot Bui, Vasant G. Honavar
2013	—	`conf`	Transportability from Multiple Environments with Limited Experiments. NIPS Elias Bareinboim, Sanghack Lee, Vasant G. Honavar, Judea Pearl
2013	A*	`conf`	m-Transportability: Transportability of a Causal Effect from Multiple Environments. AAAI Sanghack Lee, Vasant G. Honavar
2006	C	`conf`	A New Polynomial Time Algorithm for Bayesian Network Structure Learning. ADMA Sanghack Lee, Jihoon Yang, Sungyong Park
2004	B	`conf`	Discovery of Hidden Similarity on Collaborative Filtering to Overcome Sparsity Problem. Discovery Science Sanghack Lee, Jihoon Yang, Sung-Yong Park