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Contributed Papers

Dimension Reduction, Latent Structure, and Factor Modeling in Modern Data

Tue, Aug 4, 2:00 PM - 3:50 PM Room CC-254B Thomas M. Menino Convention & Exhibition Center

Yuqi GuChair

IMS

7 Presentations

Dimension Reduction for Tensor-Valued Time Series

2:05 PM - 2:20 PM

Daniel Davidson

Co-authors: S. Yaser Samadi (Southern Illinois University-Carbondale)

tensor time series dimension reduction high dimensionality structured dependence

Dimension Reduction Modeling Spatio-Temporal Data

2:20 PM - 2:35 PM

Dulari Liyanaarachchi (Southern Illinois University, Carbondale, IL)

Co-authors: S. Yaser Samadi (Southern Illinois University-Carbondale)

Spatio-temporal models Dimension reduction Quasi-likelihood estimation

Graph Frequency-Domain Factor Modeling

2:35 PM - 2:50 PM

Co-authors: Hee-Seok Oh (Seoul National University)

Dimension reduction Factor analysis Frequency domain Graph signal

Sliced Inverse Regression with Large Structural Dimensions

2:50 PM - 3:05 PM

Dongming Huang (National University of Singapore)

Co-authors: Songtao Tian (Tsinghua University), Qian Lin

central space sufficient dimension reduction structural dimension minimax rates multiple-index model

Sparse PCA: phase transitions and the near optimality of soft thresholding

3:05 PM - 3:20 PM

Michael Feldman (New York University)

Co-authors: Theodor Misiakiewicz (Yale), Elad Romanov

sparse PCA low rank recovery thresholding covariance estimation

Sufficient Dimension Reduction for High-Dimensional Multivariate Time Series

3:20 PM - 3:35 PM

S. Yaser Samadi (Southern Illinois University-Carbondale)

Co-authors: Mina Rezaei (SIUC)

Sufficient dimension reduction multivariate time series high dimensionality temporal dependence

Uncertainty Quantification for Noisy Low-tubal-rank Tensor Completion

3:35 PM - 3:50 PM

Co-authors: Jingyang Li, Yang Chen (University of Michigan)

Debiasing Spectral method Asymptotic normality

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