Description

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High-dimensional high-order/tensor data refers to data organized in the form of large-scale arrays spanning three or more dimensions, which becomes increasingly prevalent across various fields, including biology, medicine, psychology, education, and machine learning. Compared to low-dimensional or low-order data, the distinct characteristics of high-dimensional high-order data poses unprecedented challenges to the statistics community. For the most part, classical methods and theory tailored to matrix data may no longer apply to high-order data. While previous studies have attempted to address this issue by transforming high-order data into matrices or vectors through vectorization or matricization, this paradigm often leads to loss of intrinsic tensor structures, and as a result, suboptimal outcomes in subsequent analyses. Another major challenge stems from the computational side, as the high-dimensional high-order structure introduces severe computational difficulties previously unseen in the matrix counterpart. Many fundamental concepts and methods developed for matrix data cannot be extended to high-order data in a tractable manner; for instance, naive extensions of concepts such as operator norm, singular values, and eigenvalues all become NP-hard to compute. With these challenges in mind, there is an urgent need to develop new statistical methods and theory specifically tailored to handle high-dimensional high-order data.

This workshop provides an interdisciplinary platform for collaboration, facilitating the exchange of advanced research developments and topics in statistical and computational methods for analyzing tensor data. By bringing together statisticians, mathematicians, computer scientists, psychometricians, and machine learning researchers, the program aims to foster development of new interdisciplinary areas at the intersection of statistics, mathematics, psychometrics, and engineering. The workshop aims to contribute to both educational and research endeavors in these emerging fields.

Funding

Priority funding consideration will be given to those to register by March 4, 2025. Funding is limited.

Lightning Talks and Poster Session

This workshop will include lightning talks and a poster session for early career researchers (including graduate students). If accepted, you will be asked to do both. In order to propose a lightning session talk and a poster, you must first register for the workshop, and then submit a proposal using the form that will become available on this page after you register. The registration form should not be used to propose a lightning session talk or poster.

The deadline for proposing has been extended to March 20, 2025. If your proposal is accepted, you should plan to attend the event in-person.

Organizers

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Y C
Yuxin Chen University of Pennsylvania, Statistics and Data Science
Y G
Yuqi Gu Columbia University, Statistics
C M
Cong Ma University of Chicago, Statistics
A Z
Anru Zhang Duke University, Biostatistics & Bioinformatics and Computer Science

Speakers

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G A
Genevera Allen Columbia University
R C
Rong Chen Rutgers University
Y C
Yuejie Chi Carnegie Mellon University
E E
Elene Erosheva Unviersity of Washington
J F
Jianqing Fan Princeton University
R G
Rajarshi Guhaniyogi Texas A&M University
J J
Jiashun Jin Carnegie Mellon University
T K
Tracy Ke Harvard University
S K
Sunduz Keles University of Wisconsin-Madison
T K
Tamara Kolda MathSci.ai
S L
Soumendra Lahiri Washington University at Saint Louis
L L
Lexin Li University of California, Berkeley
H M
Himel Mallick Cornell University
S M
Song Mei University of California, Berkeley
A M
Andrea Montanari Stanford University
M P
Marianna Pensky Central University of Florida
C P
Carey Priebe Johns Hopkins University
A Q
Annie Qu University of California, Irvine
G R
Galen Reeves Duke University
A S
Aaron Schein University of Chicago
P S
Pixu Shi Duke University
W W S
Will Wei Sun Purdue University
M Y
Ming Yuan Columbia University
C Z
Cun-Hui Zhang Rutgers University
E Z
Emma Zhang Emory University
J Z
Ji Zhu University of Michigan

Schedule

Monday, May 5, 2025
8:30-9:00 CDT
Check-In and Breakfast
9:00-9:30 CDT
Euclidean Mirrors

Speaker: Carey Priebe (Johns Hopkins University)

9:30-9:40 CDT
Q&A
9:40-9:45 CDT
Tech Break
9:45-10:15 CDT
Spectral Ranking Inferences Based on General Multiway Comparisons

Speaker: Jianqing Fan (Princeton University)

10:15-10:25 CDT
Q&A
10:25-10:55 CDT
Coffee Break
10:55-11:25 CDT
TBA

Speaker: Tammy Kolda (MathSci.ai)

11:25-11:35 CDT
Q&A
11:35-11:40 CDT
Tech Break
11:40-12:10 CDT
Dynamic Tensor Factor Model with Main and Interaction Effects

Speaker: Rong Chen (Rutgers University)

12:10-12:20 CDT
Q&A
12:20-13:20 CDT
Lunch Break
13:20-13:50 CDT
TBA

Speaker: Jiashun Jin (Carnegie-Mellon University)

13:50-14:00 CDT
Q&A
14:00-14:05 CDT
Tech Break
14:05-14:35 CDT
TBA

Speaker: Andrea Montanari (Stanford University)

14:35-14:45 CDT
Q&A
14:45-15:15 CDT
Coffee Break
15:15-16:15 CDT
Group Activitiy
Tuesday, May 6, 2025
8:30-9:00 CDT
Check-In and Breakfast
9:00-9:30 CDT
TBA

Speaker: Cong Ma (University of Chicago)

9:30-9:40 CDT
Q&A
9:40-9:45 CDT
Tech Break
9:45-10:15 CDT
Simultaneous Decorrelation of Matrix Time Series

Speaker: Cun-Hui Zhang (Rutgers University)

10:15-10:25 CDT
Q&A
10:25-10:55 CDT
Coffee Break
10:55-11:25 CDT
TBA

Speaker: Annie Qu (University of California, Irvine)

11:25-11:35 CDT
Q&A
11:35-11:40 CDT
Tech Break
11:40-12:10 CDT
TBA

Speaker: Elena Erosheva (University of Washington)

12:10-12:20 CDT
Q&A
12:20-13:20 CDT
Lunch Break
13:20-13:50 CDT
A Statistically Provable Approach to Integrating LLMs into Topic Modeling

Speaker: Tracy Ke (Harvard University)

13:50-14:00 CDT
Q&A
14:00-14:05 CDT
Tech Break
14:05-14:35 CDT
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements

Speaker: Yuejie Chi (Carnegie-Mellon University)

14:35-14:40 CDT
Q&A
14:45-14:50 CDT
Tech Break
14:50-15:20 CDT
TBA

Speaker: Yuqi Gu (Columbia University)

15:20-15:30 CDT
Q&A
15:30-16:30 CDT
Poster Session + Social Hour
Wednesday, May 7, 2025
8:30-9:00 CDT
Check-In and Breakfast
9:00-9:30 CDT
Generalized Tensor Completion for Noisy Data with Non-Random Missingness

Speaker: Emma Zhang (Emory University)

9:30-9:40 CDT
Q&A
9:40-9:45 CDT
Tech Break
9:45-10:15 CDT
Joint Semi-Symmetric Tensor PCA for Integrating Multi-modal Populations of Networks

Speaker: Genevera Allen (Columbia University)

10:15-10:25 CDT
Q&A
10:25-10:55 CDT
Coffee Break
10:55-11:25 CDT
Tensor approaches for single cell 3D genome data analysis

Speaker: Sunduz Keles (University of Wisconsin, Madison)

11:25-11:35 CDT
Q&A
11:35-11:40 CDT
Tech Break
11:40-12:10 CDT
TBA

Speaker: Soumendra Lahiri (Washington University in St. Louis)

12:10-12:20 CDT
Q&A
12:20-13:20 CDT
Lunch Break
13:20-13:50 CDT
Tensor Data Analysis and Some Applications in Neuroscience

Speaker: Lexin Li (University of California, Berkeley (UC Berkeley))

13:50-14:00 CDT
Q&A
14:00-14:05 CDT
Tech Break
14:05-14:35 CDT
Online Tensor Inference

Speaker: Will Wei Sun (Purdue University)

14:35-14:45 CDT
Q&A
14:45-15:15 CDT
Coffee Break
15:15-16:15 CDT
Group Activity 2
Thursday, May 8, 2025
8:30-9:00 CDT
Check-In and Breakfast
9:00-9:30 CDT
TBA

Speaker: Rajarshi Guhaniyogi (Texas A&M University, College Station)

9:30-9:40 CDT
Q&A
9:40-9:45 CDT
Tech Break
9:45-10:15 CDT
Statistical inference in finite rank tensor regression models

Speaker: Galen Reeves (Duke University)

10:15-10:25 CDT
Q&A
10:25-10:55 CDT
Coffee Break
10:55-11:25 CDT
Hyperbolic Network Latent Space Model with Learnable Curvature

Speaker: Ji Zhu (University of Michigan)

11:25-11:30 CDT
Q&A
11:35-11:40 CDT
Tech Break
11:40-12:10 CDT
Can quantum algorithms bridge the statistical-computational gap in random combinatorial optimization?

Speaker: Song Mei (University of California, Berkeley (UC Berkeley))

12:10-12:20 CDT
Q&A
12:20-13:20 CDT
Lunch Break
13:20-13:50 CDT
Conformalized Tensor Regression for Fusion-Agnostic Multiview Learning

Speaker: Himel Mallick (Cornell University)

13:50-14:00 CDT
Q&A
14:00-14:05 CDT
Tech Break
14:05-14:35 CDT
TBA

Speaker: Joshua Agterberg (University of Illinois at Urbana-Champaign)

14:35-14:45 CDT
Q&A
14:45-15:15 CDT
Coffee Break
15:15-15:45 CDT
TBA

Speaker: Yuchen Zhou (University of Illinois at Urbana-Champaign)

15:45-15:50 CDT
Q&A
Friday, May 9, 2025
8:30-9:00 CDT
Check-In and Breakfast
9:00-9:30 CDT
TBA

Speaker: Aaron Schein (University of Chicago)

9:30-9:40 CDT
Q&A
9:40-9:45 CDT
Tech Break
9:45-10:15 CDT
TBA

Speaker: Pixu Shi (Duke University)

10:15-10:25 CDT
Q&A
10:25-10:55 CDT
Coffee Break
10:55-11:25 CDT
TBA

Speaker: Yuchen Wu (University of Pennsylvania)

11:25-11:35 CDT
Q&A
11:35-12:05 CDT
Tensor approach to clustering in the Diverse Multilayer Random Graph model

Speaker: Marianna Pensky (University of Central Florida)

12:05-12:15 CDT
Q&A
12:15-12:30 CDT
Brief Closing Remarks and Survey

Registration

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