Sanghack Lee
Titel
Zitiert von
Zitiert von
Jahr
Discovery of hidden similarity on collaborative filtering to overcome sparsity problem
S Lee, J Yang, SY Park
International Conference on Discovery Science, 396-402, 2004
632004
m-transportability: Transportability of a causal effect from multiple environments
S Lee, V Honavar
Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2013), 2013
232013
Transportability from multiple environments with limited experiments
E Bareinboim, S Lee, V Honavar, J Pearl
222013
On learning causal models from relational data
S Lee, V Honavar
Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), 2016
212016
Fairness in algorithmic decision making: An excursion through the lens of causality
A Khademi, S Lee, D Foley, V Honavar
The World Wide Web Conference, 2907-2914, 2019
202019
General Identifiability with Arbitrary Surrogate Experiments
S Lee, JD Correa, E Bareinboim
Thirty-fifth Conference on Uncertainty in Artificial Intelligence (UAI 2019), 2019
182019
Structural causal bandits: where to intervene?
S Lee, E Bareinboim
Advances in Neural Information Processing Systems 31 31, 2018
172018
Causal transportability of experiments on controllable subsets of variables: z-transportability
S Lee, V Honavar
Twenty-ninth Conference on Uncertainty in Artificial Intelligence (UAI 2013 …, 2013
142013
Teens are from mars, adults are from venus: analyzing and predicting age groups with behavioral characteristics in instagram
K Han, S Lee, JY Jang, Y Jung, D Lee
Proceedings of the 8th ACM Conference on Web Science, 35-44, 2016
132016
Structural Causal Bandits with Non-manipulable Variables
S Lee, E Bareinboim
Thirty-third Conference on Artificial Intelligence (AAAI 2019), 2019
82019
A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics.
S Lee, VG Honavar
Thirty-second Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016
82016
Generalized Transportability: Synthesis of Experiments from Heterogeneous Domains
S Lee, JD Correa, E Bareinboim
Thirty-fourth Conference on Artificial Intelligence (AAAI 2020), 2020
62020
Self-discrepancy conditional independence test
S Lee, VG Honavar
Thirty-third Conference on Uncertainty in Artificial Intelligence (UAI 2017), 2017
62017
Causal Effect Identifiability under Partial-Observability
S Lee, E Bareinboim
Thirty-seventh International Conference on Machine Learning, 2020
52020
A kernel conditional independence test for relational data
S Lee, V Honavar
Thirty-third Conference on Uncertainty in Artificial Intelligence (UAI 2017), 2017
32017
Lifted representation of relational causal models revisited: Implications for reasoning and structure learning
S Lee, V Honavar
UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st …, 2015
32015
Learning classifiers from distributional data
HT Lin, S Lee, N Bui, V Honavar
2013 IEEE International Congress on Big Data, 302-309, 2013
32013
Towards robust relational causal discovery
S Lee, V Honavar
Thirty-fifth Conference on Uncertainty in Artificial Intelligence (UAI 2019), 2019
12019
Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe
S Lee, E Bareinboim
Advances in Neural Information Processing Systems 33, 2020
2020
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