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Chengchun Shi

Showing results (1-10 of 27) with videos related to

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Journal of the American Statistical Association|March 22, 2023
Testing Mediation Effects Using Logic of Boolean MatricesChengchun Shi, Lexin Li
Journal of the American Statistical Association|February 12, 2019
A Massive Data Framework for M-Estimators with Cubic-RateChengchun Shi, Wenbin Lu, Rui Song
Journal of Machine Learning Research : JMLR|January 28, 2020
Determining the Number of Latent Factors in Statistical Multi-Relational LearningChengchun Shi, Wenbin Lu, Rui Song
Electronic Journal of Statistics|August 8, 2017
Robust learning for optimal treatment decision with NP-dimensionalityChengchun Shi, Rui Song, Wenbin Lu
Journal of the American Statistical Association|October 17, 2024
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial LearningChengchun Shi, Yunzhe Zhou, Lexin Li
Annals of Statistics|June 14, 2019
ON TESTING CONDITIONAL QUALITATIVE TREATMENT EFFECTSChengchun Shi, Rui Song, Wenbin Lu
Journal of the American Statistical Association|December 14, 2020
A Sparse Random Projection-based Test for Overall Qualitative Treatment EffectsChengchun Shi, Wenbin Lu, Rui Song
Annals of Statistics|September 20, 2019
LINEAR HYPOTHESIS TESTING FOR HIGH DIMENSIONAL GENERALIZED LINEAR MODELSChengchun Shi, Rui Song, Zhao Chen, et al.
Annals of Statistics|May 29, 2018
HIGH-DIMENSIONAL A-LEARNING FOR OPTIMAL DYNAMIC TREATMENT REGIMESChengchun Shi, Alin Fan, Rui Song, et al.
Journal of the Royal Statistical Society. Series B, Statistical Methodology|December 18, 2018
Maximin Projection Learning for Optimal Treatment Decision with Heterogeneous Individualized Treatment EffectsChengchun Shi, Rui Song, Wenbin Lu, et al.
Pageof 3

Showing results (1-10 of 27) with videos related to

Sort By:
Pageof 3
Journal of the American Statistical Association|March 22, 2023
Testing Mediation Effects Using Logic of Boolean MatricesChengchun Shi, Lexin Li
Journal of the American Statistical Association|February 12, 2019
A Massive Data Framework for M-Estimators with Cubic-RateChengchun Shi, Wenbin Lu, Rui Song
Journal of Machine Learning Research : JMLR|January 28, 2020
Determining the Number of Latent Factors in Statistical Multi-Relational LearningChengchun Shi, Wenbin Lu, Rui Song
Electronic Journal of Statistics|August 8, 2017
Robust learning for optimal treatment decision with NP-dimensionalityChengchun Shi, Rui Song, Wenbin Lu
Journal of the American Statistical Association|October 17, 2024
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial LearningChengchun Shi, Yunzhe Zhou, Lexin Li
Annals of Statistics|June 14, 2019
ON TESTING CONDITIONAL QUALITATIVE TREATMENT EFFECTSChengchun Shi, Rui Song, Wenbin Lu
Journal of the American Statistical Association|December 14, 2020
A Sparse Random Projection-based Test for Overall Qualitative Treatment EffectsChengchun Shi, Wenbin Lu, Rui Song
Annals of Statistics|September 20, 2019
LINEAR HYPOTHESIS TESTING FOR HIGH DIMENSIONAL GENERALIZED LINEAR MODELSChengchun Shi, Rui Song, Zhao Chen, et al.
Annals of Statistics|May 29, 2018
HIGH-DIMENSIONAL A-LEARNING FOR OPTIMAL DYNAMIC TREATMENT REGIMESChengchun Shi, Alin Fan, Rui Song, et al.
Journal of the Royal Statistical Society. Series B, Statistical Methodology|December 18, 2018
Maximin Projection Learning for Optimal Treatment Decision with Heterogeneous Individualized Treatment EffectsChengchun Shi, Rui Song, Wenbin Lu, et al.
Pageof 3