Jiji Zhang
Orcid: 0000-0003-0684-2084
According to our database1,
Jiji Zhang
authored at least 46 papers
between 2003 and 2024.
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Bibliography
2024
IEEE Trans. Neural Networks Learn. Syst., April, 2024
2023
IEEE Trans. Knowl. Data Eng., September, 2023
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective.
ACM Comput. Surv., 2023
Proceedings of the Logic, Rationality, and Interaction - 9th International Workshop, 2023
2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
On Learning Causal Structures from Non-Experimental Data without Any Faithfulness Assumption.
Proceedings of the Algorithmic Learning Theory, 2020
2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
How to Tackle an Extremely Hard Learning Problem: Learning Causal Structures from Non-Experimental Data without the Faithfulness Assumption or the Like.
CoRR, 2018
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
A Graphical Criterion for Effect Identification in Equivalence Classes of Causal Diagrams.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
2017
Int. J. Data Sci. Anal., 2017
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
2016
On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model.
ACM Trans. Intell. Syst. Technol., 2016
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
2015
2013
J. Philos. Log., 2013
2011
Discussion of "Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables".
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
2010
2008
On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias.
Artif. Intell., 2008
2007
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
A Characterization of Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables.
Proceedings of the UAI 2007, 2007
2006
Proceedings of the UAI '06, 2006
2005
A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables.
Proceedings of the UAI '05, 2005
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables.
Proceedings of the UAI '05, 2005
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005
2003
Proceedings of the UAI '03, 2003