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Contributed Papers

Tensor Learning with Neural Networks for High-Dimensional Data

Sun, Aug 2, 4:00 PM - 5:50 PM Room CC-211 Thomas M. Menino Convention & Exhibition Center

Duo YuChair

Section on Statistical Learning and Data Science

6 Presentations

A functional tensor model for dynamic multilayer networks with common invariant subspaces

4:05 PM - 4:20 PM

Runbing Zheng (Johns Hopkins University)

Co-authors: Runshi Tang, Anru Zhang (Duke University), Carey Priebe (Johns Hopkins University)

dynamic multilayer network latent space model functional network functional tensor decomposition Reproducing Kernel Hilbert Space

Dynamic Generalized Factor Models for High-Dimensional Binary Longitudinal Data

4:20 PM - 4:35 PM

Latent Space Model Longitudinal Data Electronic Health Records

Functional Autoencoders with Temporal Latent Dynamics for Forecasting

4:35 PM - 4:50 PM

Mobina Pourmoshir (Marquette University)

Co-authors: Hossein Haghbin (Persian Gulf University), Mehdi Maadooliat (Marquette University)

Functional data analysis Representation learning Functional Autoencoders Dimensionality reduction Time series modeling Latent space forecasting

Joint low-rank and individual sparse modeling for multi-response matrix-variate trace regression

4:50 PM - 5:05 PM

Daeyoung Ham (University of Texas San Antonio)

Co-authors: Brad Price (West Virginia University)

Low-rank plus sparse decomposition Multivariate generalized linear models Matrix-variate predictors Joint structure learning

Sparse Kernel Regression for High-Dimensional Nonlinear Time Series

5:05 PM - 5:20 PM

Adam Waterbury (Denison University)

Co-authors: Marie-Christine Duker (Cornell University)

time series reproducing kernel Hilbert space nonlinear dynamics concentration inequality high-dimensional sparse

The Generalized Multilinear Model for High Dimensional Tensor-on-Tensor Regression

5:20 PM - 5:35 PM

Carlos Llosa (Sandia National Laboratories)

Co-authors: Danny Dunlavy (Sandia National Laboratories), Richard B. Lehoucq (Sandia National Laboratories), Tian Ma (Sandia National Laboratories), Jeremy Myers (Sandia National Laboratories), Gavin Collins

low-rank tensors generalized linear models tensor decompositions supervised learning high dimensional regression positron emission tomography PET

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