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204 Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-140A
Statistical Computing by Deep Learning and Penalization — Contributed Papers
Section on Statistical Computing
Chair(s): David Shilane, Columbia University
2:05 PM A Penalized Poisson Likelihood Approach to High-Dimensional Semiparametric Inference of Doubly-Stochastic Point Processes
Si Cheng, University of Washington; Ali Shojaie, University of Washington
2:20 PM Efficient Computation of High-Dimensional Penalized Generalized Linear Mixed Models by Latent Factor Modeling of the Random Effects
Hillary M. Heiling, University of North Carolina Chapel Hill; Naim U. Rashid, University of North Carolina Chapel Hill; Quefeng Li, University of North Carolina Chapel Hill; Joseph G Ibrahim, University of North Carolina
2:35 PM Efficient Large-Scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks
Pratik Nag, King Abdullah University of Science and Technology; Sameh Abdulah, KAUST; Yiping Hong, King Abdullah University of Science and Technology; Marc Genton, KAUST; Ying Sun, KAUST; Ghulam Qadir, Heidelberg Institute of Theoretical Studies
2:50 PM Vulnerabilities of Learning Models Under Malicious Data and Attack Against Deep Neural Networks
Bowei Xi, Purdue University
3:05 PM Virtual Testing Failure Analysis Using Neural Networks and Gaussian Processes
Thomas Muehlenstaedt, ArgoAI; Roman Nagy, Argo AI
3:20 PM Sparse Envelope Quantile Model
Hossein Moradi Rekabdarkolaee, South Dakota State University
3:35 PM Features Extraction via Bayesian Analyses Cum Mixture Probabilistic Models by Extensive Computations
Humayun Kiser, Comilla University; Mian Arif Shams Adnan, Bowling Green State University