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Contributed Papers

Structure Learning and Dimension Reduction

Sun, Aug 3, 4:00 PM - 5:50 PM Room CC-102B Music City Center

Hon Yiu SoChair

Section on Statistical Learning and Data Science

7 Presentations

Association Structure Learning in Multivariate Categorical Response Regression

4:05 PM - 4:20 PM

Co-authors: Hongru Zhao, Adam Rothman (University of Minnesota), Hongru Zhao, Aaron Molstad (University of Minnesota)

multinomial logistic regression categorical data analysis log-linear models

Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction

4:20 PM - 4:35 PM

Co-authors: Yin Tang, Bing Li (Penn State University), Yin Tang

Autoencoder Convergence rate Covering numbers Deep learning Probability characterizing family

Covariate-assisted Grade of Membership Model

4:35 PM - 4:50 PM

Co-authors: Zhiyu Xu (Columbia University), Zhiyu Xu (Columbia University), Yuqi Gu (Columbia University)

Grade of Membership Model Identifiability Sequential Projection Algorithm Covariate Assistance Spectral Method

Federated multimodal learning with heterogeneous modality and distribution shift

4:50 PM - 5:05 PM

Co-authors: Dazheng Zhang, Dazheng Zhang, Huiyuan Wang (University of Pennsylvania), Jingyue Huang, Yong Chen (University of Pennsylvania, Perelman School of Medicine)

Causal inference Negative control outcomes Average treatment effect Bias Correction Multi-Modality

Meta-Fusion: A Unified Framework For Multi-modality Fusion with Mutual Learning

5:05 PM - 5:20 PM

Co-authors: Ziyi Liang, Ziyi Liang, Annie Qu (University of California At Irvine), Babak Shahbaba (UCI)

multi-modality fusion deep mutual learning ensemble learning soft information sharing

Principal Subsimplex Analysis

5:20 PM - 5:35 PM

Co-authors: Hyeon Lee, James Marron (University of North Carolina at Chapel Hill), Hyeon Lee, Janice Scealy (Australian National University), Andrew Wood (The Australian National University), Eric Grunsky (University of Waterloo), Kassel Hingee (Australian National University)

Modes of variation Backwards approach Nested relations Compositional data Paleoceanography

Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence

5:35 PM - 5:50 PM

Co-authors: Runshi Tang, Runshi Tang, Julien Chhor, Olga Klopp, Anru Zhang (Duke University)

tensor CP decomposition alternative least square statistical bound

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