Sanghack Lee
28 papers · 2013–2026 · 8 venues · across top CS/AI venues
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Research topics
Artificial Intelligence
(26)
Core AI
(26)
Machine Learning
(18)
Learning Types Β· Machine Learning
(10)
Knowledge & Reasoning
(6)
Application Areas
(6)
Reasoning
(6)
Deep Learning
(4)
Optimization & Theory
(4)
Core Methods
(3)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(3)
Mathematics & Optimization
(2)
Reinforcement Learning
(2)
Methods
(2)
Keywords
causal inference
(13)
causal discovery
(5)
structural causal model
(3)
causal graph
(3)
graphical model
(3)
causal effect
(3)
causal identifiability
(3)
multi-armed bandit
(3)
conditional independence test
(3)
causal bandit
(2)
do calculus
(2)
causal transportability
(2)
sample efficiency
(2)
interventional distribution
(2)
heterogeneous domains
(2)
data augmentation
(2)
domain generalization
(2)
causal structure
(2)
structure learning
(2)
conditional independence
(2)
Papers
Beyond Bounds: Quantifying the Probability of Counterfactual Fairness
UAI 2026
Breaking Bad: Component-Wise Parent Deletion for Score-Based Causal Discovery
UAI 2026
Canonical Domain Reduction for Partial Counterfactual Identification
UAI 2026
Donβt Test What You Can Deduce: Causal Discovery with Logical Inference
UAI 2026
Estimating Interventional Outcomes over Time with Causal Normalizing Flow
UAI 2026
Mitigating Length Bias in RLHF Through a Causal Lens
AAAI 2026
On Causal Representation Learning with Internal Auxiliaries
UAI 2026
On Transportability for Structural Causal Bandits
UAI 2026
PEER Pressure: Model-to-Model Regularization for Single Source Domain Generalization
CVPR 2025
Causal Discovery with Deductive Reasoning: One Less Problem
UAI 2024
Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference
NeurIPS 2024
Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
UAI 2024
Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models
AISTATS 2024
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
ICML 2024
On Positivity Condition for Causal Inference
ICML 2024
On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition
CLeaR 2023
Counterfactual Transportability: A Formal Approach
ICML 2022
SNU-Causality Lab @ Causal News Corpus 2022: Detecting Causality by Data Augmentation via Part-of-Speech tagging
EMNLP 2022
Causal Identification with Matrix Equations
NeurIPS 2021
Nested Counterfactual Identification from Arbitrary Surrogate Experiments
NeurIPS 2021
Causal Effect Identifiability under Partial-Observability
ICML 2020
Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe
NeurIPS 2020
General Transportability β Synthesizing Observations and Experiments from Heterogeneous Domains
AAAI 2020
General Identifiability with Arbitrary Surrogate Experiments
UAI 2019
Structural Causal Bandits with Non-Manipulable Variables
AAAI 2019
Towards Robust Relational Causal Discovery
UAI 2019
Structural Causal Bandits: Where to Intervene?
NeurIPS 2018
Transportability from Multiple Environments with Limited Experiments
NeurIPS 2013