Search Research Symposium Abstracts

Applications of DCA in Solving Multifacility Location Problems Based on Mixed Integer Programming

The talk introduces a new approach to solve multifacility location problems based on mixed integer programming and algorithms for minimizing differences of convex (DC) functions. This class of multifacility location problems is very difficult to solve because of its intrinsic discrete, nonconvex, and nondifferentiable nature. We first reformulate the problem [Read More...]

Presenter: Tuyen Tran, Loyola University Chicago
Authors: Tuyen Tran, Anuj Bajaj, Mau Nam Nguyen, Boris Mordukhovich
Symposium Year: 2023
Session: Women in Tensor Optimization [Organized by Longxiu Huang and Jing Qin]
Presentation Time: September 30, 2023; 2:00 pm

Optimal Matrix-Mimetic Tensor Algebras via Variable Projection

Many data are naturally represented as multiway arrays or tensors, and as a result, tensor-based approaches have revolutionized data analysis, feature extraction, and data compression tasks. Despite the success, high-dimensional data analysis tools suffer from a so-called "curse of multidimensionality;" that is, that fundamental linear algebra [Read More...]

Presenter: Elizabeth Newman, Emory University
Authors: Elizabeth Newman, Katherine Keegan
Symposium Year: 2023
Session: Women in Tensor Optimization [Organized by Longxiu Huang and Jing Qin]
Presentation Time: September 30, 2023; 2:25 pm

Low-rank tensor recovery from memory-efficient measurements

Data-oblivious measurements present an important branch of low-rank data compression and recovery techniques, frequently used in streaming settings and within iterative algorithms. Typically, linear data-oblivious measurements involve some version of a random sketch that preserves the geometric properties of the data. When data is tensorial, a special [Read More...]

Presenter: Liza Rebrova, Princeton University
Symposium Year: 2023
Session: Women in Tensor Optimization [Organized by Longxiu Huang and Jing Qin]
Presentation Time: September 30, 2023; 2:50 pm

A novel tensor regularization of nuclear over Frobenius norms for low rank tensor recovery

We consider low-rank tensor recovery problems that include low-rank tensor completion (LRTC) and tensor robust principal component analysis (TRPCA). Based on the tensor singular value decomposition (t-SVD), we propose the ratio of the tensor nuclear norm and the tensor Frobenius norm (TNF) as a novel nonconvex surrogate of tensor's tubal rank in LRTC [Read More...]

Presenter: Yifei Lou, University of Texas at Dallas
Authors: Huiwen Zheng, Guoliang Tian, and Chao Wang
Symposium Year: 2023
Session: Women in Tensor Optimization [Organized by Longxiu Huang and Jing Qin]
Presentation Time: September 30, 2023; 3:15 pm

Nonnegative and Nonlocal Sparse Tensor Factorization-Based Hyperspectral Image Super-Resolution

Hyperspectral image (HSI) super-resolution refers to enhancing the spatial resolution of a 3-D image with many spectral bands (slices). It is a seriously ill-posed problem when the low-resolution (LR) HSI is the only input. It is better solved by fusing the LR HSI with a high-resolution (HR) multispectral image (MSI) for a 3-D image with both [Read More...]

Presenter: Weihong Guo, Case Western Reserve University
Authors: Wei Wan, Weihong Guo, Haiyang Huang, and Jun Liu
Symposium Year: 2023
Session: Women in Tensor Optimization [Organized by Longxiu Huang and Jing Qin]
Presentation Time: September 30, 2023; 3:40 pm