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Beyond Gaussian Approximation: Bootstrap Methods for Maxima of Sums, Hang Deng, Rutgers University (12/11/20)
Hypothesis Testing for Large-Scale Data: Enhancing Reliability and Efficiency, Yinqiu He, University of Michigan (12/16/20)
Transparent and robust causal inferences in data science, Carlos Cinelli, UCLA (12/17/20)
A few recovery problems from noisy observations, Xiaoqian (Dana) Yang, Duke University (12/18/20)
Astronomical instrument calibration with mean-variance coupled models, Yang Chen, University of Michigan (12/21/20)
Statistical inference for multiple network data, Jesus Arroyo, University of Maryland (01/08/21)
Instrumental Variable Approaches to Individualized Treatment Regimes under Endogeneity, Yifan Cui, University of Pennsylvania (01/11/21)
Power Enhancement in High-Dimensional Hypothesis Testing, Xiufan Yu, Penn State University (01/12/21)
Frequentist Validation of Bayesian Uncertainty Quantification, Subhashis Ghoshal, North Carolina State University (01/14/21)
Big Data: A Perspective from Statistical Foundation of Data Science, Tapabrata Maiti, Michigan State University (01/15/21)
Integrating computational physics and numerical optimization to address challenges in science, engineering, and medicine, Matthew Zahr, University of Notre Dame (04/05/21)
A functional data analysis study of stratospheric ozone trends, and ozonesonde measurement biases, Wendy Meiring, University of California, Santa Barbara (04/12/21)
Inferring Biological Functions with Explainable Algorithms, Amirali Aghazadeh, University of California, Berkeley (04/19/21)
Video access is restricted to members of the ACMS Department.